CN113777914B - Control distribution method with intelligent fault detection and correction functions - Google Patents
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Abstract
The invention discloses a control distribution method with intelligent fault detection and correction functions, and belongs to the field of automation and control. The implementation method of the invention comprises the following steps: distributing the total control instruction to each controller in real time through a control distribution algorithm; comparing the difference between the actual output control quantity and the instruction control quantity of each executing mechanism to judge whether the executing mechanism fails or not and determine a corresponding failure mode model; and carrying out intelligent correction and elimination on faults by real-time input of a correction control distribution algorithm aiming at each fault mode. The invention converts the control allocation problem into the weighted least square problem, and adopts the weighted least square problem of the control allocation solved by the effective set algorithm method, thereby improving the control allocation efficiency. The invention can effectively detect the faults in real time when the faults occur, corrects the faults by optimizing control distribution parameters, ensures the safety and reliability of the system, and has the advantages of good instantaneity, high execution efficiency, high control precision and strong robustness.
Description
Technical Field
The invention discloses a control distribution method with intelligent fault detection and correction functions, relates to a control distribution method for intelligently detecting and correcting faults by a system under the condition that a control system executing mechanism generates faults, and belongs to the field of automation and control.
Background
With the rapid development of modern science and industrial technology, the automation degree of engineering fields such as aerospace, navigation, automobiles and robots is increasing, and in order to ensure the reliability and safety of industrial systems, overdrive control systems are widely used. The overdrive control system is a system with the number of executing mechanisms larger than the control dimension required by completing tasks, taking spacecraft attitude control in the field of spaceflight as an example, momentum wheels are often arranged on the spacecraft to control the attitude of the system in three dimensions of pitching, yawing and rolling, and modern spacecraft are often provided with 4-5 or more momentum wheels to ensure the reliability of the system, so that the spacecraft is the overdrive system; in addition, an aircraft with multiple groups of control surfaces and an automobile with multiple driving modes are all overdrive systems. The overdrive system needs to be designed to effectively control the distribution method to rapidly and accurately distribute the control command generated by the controller to each executing mechanism, and ensure that the vector sum of the actual control quantity (such as resultant force or resultant moment generated by a plurality of thrusters of a plurality of spacecrafts) generated by each executing mechanism under the condition of constraint (such as amplitude constraint or rotation angle constraint) and the control command are minimum, so that the best control effect is achieved. In practical engineering application, the execution mechanism may generate various types of faults, if the faults are not detected and eliminated in time, the whole control system can be greatly influenced, even the complete failure of the system is caused, the smooth progress of tasks and the life safety of personnel are threatened, and higher requirements on fault tolerance and reliability are provided for the design of the control system; when a fault occurs, the control system needs to discover the occurrence of the fault in time, locate the executing mechanism with the fault, intelligently judge the type of the fault and then pertinently correct the fault so as to avoid the risk caused by the fault. Therefore, the research of the intelligent control distribution method capable of detecting faults in real time and correcting the faults in time has very important significance.
Disclosure of Invention
The overdrive system is provided with a plurality of execution mechanisms, and each execution mechanism is required to generate a desired control quantity through efficient cooperative coordination; in this process, each actuator may fail in multiple modes at any time, thereby threatening the safety of the system. Aiming at the technical problems, the invention aims to provide a control distribution method with intelligent fault detection and correction functions, which distributes total control instructions to each controller in real time through a control distribution algorithm on the basis of defining a control system dynamics model and a control law; judging whether the executing mechanism fails or not by classifying and summarizing the executing mechanism failure mode models and comparing the difference between the actual output control quantity and the instruction control quantity of each executing mechanism, and determining the corresponding failure mode model to realize the detection of the executing mechanism failure; and carrying out intelligent correction and elimination on faults by real-time input of a correction control distribution algorithm aiming at each fault mode. The invention can effectively detect the faults in real time when the faults occur, corrects the faults by optimizing control distribution parameters, ensures the safety and reliability of the system, and has the advantages of good instantaneity, high execution efficiency, high control precision and strong robustness. In addition, when a control distribution algorithm is designed, the control distribution problem is converted into a weighted least square problem, and the weighted least square problem of the control distribution is solved by adopting an active set algorithm method, so that the control distribution efficiency is improved. The invention is widely applied to the industrial fields of aerospace, aviation, automobiles, ships, robots and the like.
The aim of the invention is achieved by the following technical scheme.
The invention discloses a control distribution method with intelligent fault detection and correction functions, which is mainly realized based on a control distribution module and an intelligent fault detection and correction module, wherein the control distribution module distributes a total control instruction to each executing mechanism in real time by executing a control distribution algorithm. The intelligent fault detection and correction module is used for intelligently judging whether the executing mechanism generates faults or not and generating fault modes by sensing the actual output control quantity of the executing mechanism in real time and comparing the actual output control quantity with the command signal, and intelligently correcting and removing the faults by correcting the real-time input of the control distribution module aiming at each fault mode so as to ensure that the working state of the system is not influenced by the faults.
The invention discloses a control distribution method with intelligent fault detection and correction functions, which comprises the following steps:
Step one: and constructing an integral closed-loop model of the control system, defining all parameters required in the control process, defining basic functions and control parameter definitions of all parts of the control system, and building a dynamics model and a control law of the control system.
Step 1.1: and constructing a complete control system closed-loop model formed by a virtual instruction layer and a physical system layer, and determining the physical meaning of the function and each parameter of each part.
The complete control system closed loop is composed of a physical system layer and a virtual instruction layer. The physical system layer refers to the physical entities of the control system, including actuators, loads, and platforms that produce control quantities. The virtual instruction layer refers to a control algorithm carried in the electronic equipment, and mainly senses the motion state of a physical entity through a sensor to make a decision so as to generate a control instruction. The virtual instruction layer senses the motion state of the physical entity and generates a control instruction, the execution mechanism outputs corresponding control quantity to change the motion state of the physical entity, and the motion state of the physical entity is sensed by the virtual instruction layer, so that the closed-loop control system is formed.
Each actuator of the physical system layer receives a virtual actuator instruction issued by the control allocation module, the virtual actuator instruction is defined as u d, the output actual actuator control quantity is defined as u a, wherein u d and u a are expressed by m×1-dimensional vectors, m is the number of the actuators, and the i (i=1, 2, … m) component of the vector corresponds to the actuator with the number i. U a＝ud should be satisfied in the case of no failure of the actuator, but u a≠ud is present in the case of failure of the actuator.
The installation matrix of the execution mechanism can be determined according to the installation position and the installation angle of each execution mechanism, and is defined as B a, and is an n multiplied by m dimensional matrix, wherein n is the dimension of the total control quantity of the system, the total control quantity acting on the physical system is obtained through u a and B a, and is defined as T a, and the calculation formula is as follows:
Ta＝Baua (1)
Under the action of the total control quantity, the physical system generates corresponding motion according to dynamics, namely a physical rule of motion, and the generated actual motion state is represented by x a(1×n).
After the virtual instruction layer senses the actual motion state x a of the physical system through the sensor, the virtual instruction layer is compared with the expected motion state x d(1×n) of the physical system, and when the actual motion state does not reach the expected motion state, the control law module generates a virtual total control instruction according to the designed control law and is represented by T c(1×n). Only when the total control command T c is equal to the actual total control quantity T a acting on the physical entity in real time, i.e. the control quantity error therebetween satisfies: e T＝Tc-Ta =0, the control effect can be achieved. The functions of the control distribution module and the intelligent fault detection and correction module are to ensure that the control quantity error is quickly zeroed under the condition that an actuating mechanism fails: e T →0.
The intelligent fault detection and correction module judges whether the execution mechanism generates faults or not by comparing the command u d obtained by each execution mechanism with the command u a actually output by each execution mechanism, determines the number of the execution mechanism with the faults and a specific fault mode, and can intelligently generate corrected command parameters according to the specific fault mode: virtual correction assembly matrix B v(n×m) and virtual compensation torque T f(1×n). The virtual total control command and the virtual compensation torque are differenced to obtain a virtual distribution torque v d(1×n), and the virtual distribution torque v d(1×n) meets the following conditions under the condition that all executing mechanisms do not generate saturation:
vd＝Tc-Tf＝Bvud (2)
v d and B v are inputs of the control distribution module, and since the executing mechanism has upper and lower output limits, it cannot be guaranteed that all control conditions meet the equation relation of the formula (2), and the control distribution module is used for calculating the optimal u d through the control distribution algorithm so that v d-Bvud is 0 and giving an instruction to the executing mechanism.
Step 1.2: and establishing a control system dynamics model and a control law.
Describing a control system dynamics model with differential equations, expressed as:
where a (n×n) is the state transition matrix of the system, Representing the derivative of x a with respect to time. Establishing a PID control law according to a state error e x＝xd-xa of the system, wherein the PID control law is expressed as:
Where K p,Kd,Ki represents the proportional, differential and integral coefficients, respectively. The system state error is converged to 0 in a short time by the PID control law, namely: e x →0.
Step two: and establishing a control allocation module for allocating the total control instruction to each execution mechanism in real time.
Preferably, in the control allocation module, the control allocation problem is converted into a weighted least square problem, and the weighted least square problem of the control allocation is solved by adopting an active set algorithm method, so that the control allocation efficiency is improved. The implementation method of the second step is as follows:
step 2.1: in the control allocation module, the control allocation problem is converted into a weighted least squares problem.
The upper and lower bounds of the actuator are defined as u max(1×m) and u min(1×m), respectively, and their ith element represents the maximum or minimum output value of the actuator numbered i, so the actuator output command generated during the control allocation must be between the upper and lower bounds, which satisfies both the constraints:
umin≤ud≤umax (5)
And the actuator has an optimal operating state, defined as u p(1×m). The expression incorporating the weighted least squares method describes the performance index of the control allocation problem:
J＝||wu(ud-up)||2+γ||wv(Bvud-vd)||2 (6)
Wherein w u(m×m),wv(n×n) is a weighting matrix for the working condition of the executing mechanism and the control distribution efficiency, and gamma is a weighting coefficient for the control distribution. The performance index describes the degree of deviation of the desired actuator output control amount from the desired total control amount and the optimal operating state of the actuator, and takes the total control amount precision and the optimal operating condition into consideration, and measures the importance degree between the two factors by introducing a weighting matrix and a coefficient. To satisfy the accuracy priority of the total control amount, γ is set to a coefficient of one order of magnitude larger. The performance index shown in formula (6) is transformed into:
the control allocation problem is then described as:
Namely: under the condition that the upper limit and the lower limit of the output of the executing mechanism are met, the control distribution problem is converted into the weighted least square problem, so that the performance index of the weighted least square form reaches the minimum value, and the highest precision of the total control quantity is obtained.
Step 2.2: the weighted least square problem of control distribution solved by an active set algorithm method is adopted, the control distribution efficiency is improved, and the instruction control quantity u d of the executing mechanism is quickly and accurately obtained and issued to each executing mechanism.
Defining an effective set as W s(1×m), and when the execution mechanism with the number of i is used, the instruction control quantity of the execution mechanism meets the following conditions: u min(i)≤ud(i)≤umax (i), then the active set ith element satisfies: w s (i) =0; when u d(i)＝umax (i), there is W s (i) =1, when u d(i)＝umin (i), there is W s (i) = -1. The solving steps of the active set method are as follows:
Step 2.2.1: the initial value u d 0 (1×m) is selected, and the following conditions are satisfied: u min≤ud 0≤umax, setting the initial active set W s 0＝[0 … 0]T (1×m), and making the number of loops k=0. Defining a residual r=b-a uud K.
Step 2.2.2: columns of a u corresponding to non-0 elements in the active set W s K are removed from a u, Resulting in a new a u * (e.g., the first element in the active set is 1, i.e., W s (1) =1, then the first column a u of a u (1) is culled from a u, Columns 2 to m of A u form the new matrix, A u *＝Au (: 2:m)), and the pseudo-inverse A u *+, Defining an allocation disturbance value p=A u *+ R, eliminating p elements corresponding to non-0 elements in the active set W s K from p, a new p * is obtained. u d opt＝ud K+p* is calculated.
Step 2.2.3: judging whether u d opt meets the following conditions: u min≤ud opt≤umax, if yes, jump to step 2.2.4, otherwise jump to step 2.2.7.
Step 2.2.4: updating residual errors: r=r-a u * p, the lagrangian is calculated: λ=w s K·(Au T R), determine whether the lagrangian satisfies: lambda >0 (i.e. each element in lambda is greater than 0), if step 2.2.5 is met, otherwise step 2.2.6 is skipped.
Step 2.2.5: the result of the control allocation problem is found, let u d＝ud opt end the algorithm.
Step 2.2.6: u d K+1＝ud opt is calculated, and the element in W s K corresponding to the minimum element in lambda is changed to 0. Let k=k+1, return to step 2.2.2.
Step 2.2.7: defining a distance matrix:
The smallest element D min in the D matrix is defined as satisfying: u min≤ud K+αp*≤umax, the minimum step α min, calculates u d K +1＝ud K+αmin p, and changes the element in W s K corresponding to the column in which D min is located to sign (D min). Let k=k+1, return to step 2.2.2.
According to the effective set algorithm, the instruction control quantity u d of the executing mechanism can be quickly and accurately obtained and issued to each executing mechanism.
Step three: classifying the fault modes of the execution mechanism into three fault mode models of complete failure, amplitude clamping and efficiency reduction; and an intelligent fault detection and correction module is established, the actual output control quantity of the execution mechanism is perceived in real time through the intelligent fault detection and correction module and is compared with the instruction control quantity, whether the execution mechanism generates faults or not and the fault generation mode are intelligently judged, and the faults are intelligently corrected and removed according to each fault mode through the real-time input of the correction control distribution module, so that the working state of the system is not influenced by the faults.
Step 3.1: and classifying the fault modes of the execution mechanism into three fault mode models of complete failure, amplitude jamming and efficiency reduction.
The operating state of the actuator, that is, the relation between the actual control amount u a output by the actuator and the received virtual control instruction u d, may be expressed as:
ζ (1×m) is the actuator fault factor, Is the fault magnitude. When ζ=ones (1, m) andWhen the elements in zeta are all 1,When the elements in the system are all 0, no actuating mechanism fails, and the system works normally to meet u a＝ud.
When ζ (i) =0,When the actuating mechanism with the number i has a complete failure fault mode, namely the actuating mechanism cannot generate any control quantity output and cannot be used any more.
When ζ (i) =0,In the process, the actuating mechanism with the number i has an amplitude jamming fault mode, namely the control quantity output by the actuating mechanism is always kept at a fixed value C, and cannot be adjusted.
When 0< ζ (i) <1,When the actuating mechanism numbered i generates a performance reduction fault mode, namely the control quantity actually output by the actuating mechanism is always smaller than the command control quantity received by the actuating mechanism.
Step 3.2: the intelligent fault detection and correction module senses the actual output control quantity of the executing mechanism in real time and compares the actual output control quantity with the instruction signal, intelligently judges whether the executing mechanism generates faults and generates fault modes, intelligently corrects and eliminates the faults according to each fault mode through the real-time input of the correction control distribution module, and ensures that the working state of the system is not affected by the faults.
Sequentially detecting the 1 st to the m-th execution mechanisms in each closed-loop control cycle, and firstly detecting whether the execution mechanisms fail or not, namely whether u a(i)＝ud (i) is met or not (i=1, 2 … m); if yes, the executing mechanism has no fault, and the next executing mechanism is continuously detected; if not, the executing mechanism fails, and the failure mode is judged; firstly judging whether a complete failure fault mode is generated and correcting; if the complete failure fault mode does not occur, judging whether the amplitude jamming fault mode is generated and correcting; if the amplitude jamming fault mode does not occur, judging that the efficiency is reduced, correcting and starting to detect the next actuating mechanism until intelligent fault detection and correction are completed on all actuating mechanisms, inputting corrected parameters into a control distribution module to distribute total control quantity, and completing single closed-loop control. And performing circulation control according to the single closed-loop control to ensure that the working state of the system is not affected by faults.
The method for judging whether the complete failure fault mode is generated and correcting is as follows:
When u a(i)≠ud(i),ua (i) =0 is detected, that is, the output value of the executing mechanism is different from the instruction value, and the output value is 0, the executing mechanism is judged to have a complete failure fault mode.
When the execution mechanism generates a complete failure fault mode, the following adjustment is made on the input value of the control distribution module:
Let T f＝0,vd＝Tc, and B v＝[Ba(:,1:i),0(n×1),Ba (: i+ 1:m) ].
I.e., T c as the virtual control split torque v d, all elements of the i-th column of the actual assembly matrix B a are replaced with zeros as B v, and v d and B v are input to the control split module.
Proof of validity for complete failure mode correction:
The matrix formed by the ith column to the jth column of the K matrix is denoted by K (: i: j), and the matrix formed by the ith row to the jth row of the K matrix is similarly denoted by K (i: j). The column vector formed by the ith column of the K matrix is denoted by K (: i), and the row vector formed by the ith row of the K matrix is similarly denoted by K (i,:). If K is a column vector or a row vector, K (i: j) represents a column vector or a row vector formed by the ith element to the jth element of the K vector. 0 k×1 and 0 1×k represent the full 0 column vector and row vector, respectively, of the k dimension.
U d＝Bv +vd is obtained from v d＝Bvud, where B v + represents the pseudo-inverse of B v, and u a (i) =0
Then
As can be seen from the formula (11), after the fault correction, even if the execution mechanism has a complete failure fault mode, the actual control quantity T a acting on the physical system is ensured to be equal to the control law generation instruction control quantity T c, namely, the following conditions are satisfied: e T＝Tc-Ta = 0, indicating that correction of the complete failure mode is effective by adjusting the input parameters of the control distribution module.
The method for judging whether the amplitude jamming fault mode is generated or not and correcting the amplitude jamming fault mode comprises the following steps:
When u ai≠udi,uai(K)＝uai (K-1) =const is detected, that is, the output value of the actuator is not equal to the command value, and the output value of the actuator is equal to a constant value which is not equal to 0 in the previous closed-loop control cycle, it can be determined that the amplitude jamming fault mode occurs in the actuator.
When the executing mechanism generates an amplitude clamping fault mode, the following adjustment is made on the input value of the control distribution module:
Order the V d＝Tc-Tf, and
I.e. T c and virtual compensation momentAs virtual control distribution moment v d, replacing all elements of the ith column of the actual assembly matrix B a with zeros as B v, and v d and B v as inputs to the control distribution module.
Demonstration of effectiveness of correction for amplitude stuck fault pattern:
u d＝Bv +vd is obtained from v d＝Bvud, Can be obtained
Then
As shown in the formula (13), after the fault correction, even if the executing mechanism generates an amplitude jamming fault mode, the actual control quantity T a acting on the physical system can be ensured to be equal to the control law generation instruction control quantity T c, namely, the following conditions are satisfied: e T＝Tc-Ta = 0, indicating that correction of the amplitude stuck fault mode by adjusting the input parameters of the control distribution module is effective.
The method for judging whether the efficiency reduction fault mode is generated and correcting is as follows:
When u a(i)≠ud(i),0<|uai|<|udi is detected, that is, the output value of the executing mechanism is different from the instruction value, and the absolute value of the output value is smaller than the absolute value of the instruction value, it can be determined that the executing mechanism has a performance reduction fault mode at the moment.
When the execution mechanism generates the efficiency reduction fault mode, the following adjustment is made on the input value of the control distribution module:
Let T f＝0,vd＝Tc, and B v＝[Ba(:,1:i+1),(uai/udi)Ba(i),Ba (: i+ 1:m) ].
I.e., T c as the virtual control split torque v d, multiplying all elements of the i-th column of the actual assembly matrix B a by a factor δ= (u ai/udi), and v d and B v as inputs to the control split module.
Demonstration of effectiveness of reduced efficacy failure mode correction:
From v d＝Bvud, u d＝Bv +vd, from u a(i)＝σud (i)
Then
As can be seen from the formula (15), after the fault correction, even in the case where the performance reduction fault mode occurs in the actuator, the actual control amount T a acting on the physical system is ensured to be equal to the control law generation instruction control amount T c, that is, to satisfy: e T＝Tc-Ta = 0, indicating that correction of the performance-reducing failure mode by adjusting the input parameters of the control distribution module is effective.
The third step fully describes the functions of the intelligent fault detection and correction module and proves the effectiveness of the intelligent fault detection and correction module.
The beneficial effects are that:
1. The overdrive system is provided with a plurality of execution mechanisms, and each execution mechanism is required to generate a desired control quantity through efficient cooperative coordination; in this process, each actuator may fail in multiple modes at any time, thereby threatening the safety of the system. Aiming at the technical problems, the control distribution method with intelligent fault detection and correction functions disclosed by the invention classifies and summarizes the fault mode models of the execution mechanism into three fault mode models of complete failure, amplitude jamming and efficiency reduction by classifying and summarizing the fault mode models of the execution mechanism, and designs detection and correction methods corresponding to the three fault mode models of the execution mechanism; and an intelligent fault detection and correction module is established based on the detection and correction method, the actual output control quantity of the execution mechanism is perceived in real time through the intelligent fault detection and correction module and is compared with the instruction signal, whether the execution mechanism generates faults or not and the mode of generating the faults are judged intelligently, the faults are corrected and removed intelligently according to each fault mode through the real-time input of the correction control distribution module, and the working state of the system is guaranteed not to be affected by the faults.
2. The invention discloses a control distribution method with intelligent fault detection and correction functions, which converts a control distribution problem into a weighted least square problem on the basis of defining a control system dynamics model and a control law, and adopts an effective set algorithm method to solve the weighted least square problem of the control distribution; and a control distribution module is established based on the control distribution algorithm, and the total control instruction is distributed to each executing mechanism in real time through the control distribution module, so that the control distribution efficiency is improved.
3. On the basis of realizing the beneficial effects 1 and 2, the control distribution method with the intelligent fault detection and correction function disclosed by the invention has the advantages of good instantaneity, high execution efficiency, high control precision and strong robustness, and can be widely applied to the industrial fields of aerospace, aviation, automobiles, ships, robots and the like.
Drawings
FIG. 1 is a schematic diagram of a closed loop of a control system of the present invention;
FIG. 2 is a flow chart of a control distribution method with intelligent fault detection and correction functions disclosed in the present invention;
FIG. 3 is a graph of output torque of each flywheel without employing an intelligent fault detection and correction module in accordance with the present invention;
FIG. 4 is a graph of actual total torque output without employing an intelligent fault detection and correction module in accordance with the present invention;
FIG. 5 is a graph of the error between the actual total torque output and the commanded total torque without using the intelligent fault detection and correction module according to the present invention;
FIG. 6 is a graph of angular velocity change without employing an intelligent fault detection and correction module in accordance with the present invention;
FIG. 7 is a graph of the change in attitude angle without the intelligent fault detection and correction module of the present invention;
FIG. 8 is a graph of output torque of each flywheel using the intelligent fault detection and correction module of the present invention;
FIG. 9 is a graph of actual total torque output using an intelligent fault detection and correction module in accordance with the present invention;
FIG. 10 is a graph of actual total torque output versus commanded total torque error for the present invention using an intelligent fault detection and correction module;
FIG. 11 is a graph of angular velocity change using an intelligent fault detection and correction module in accordance with the present invention;
FIG. 12 is a graph of the change in attitude angle of the present invention using an intelligent fault detection and correction module.
Detailed Description
For a better description of the objects and advantages of the present invention, reference is made to the following detailed description of the embodiments of the invention taken in conjunction with the accompanying drawings. In the specific implementation mode, a specific control system in engineering is taken as an example, and the effectiveness of the invention is verified in a simulation mode. Simulation was performed in Matlab environment using Simulink tools.
Example 1:
as shown in fig. 1 and 2, the control distribution method with intelligent fault detection and correction functions disclosed in this embodiment is mainly implemented based on a control distribution module and an intelligent fault detection and correction module, and the control distribution module distributes the total control instruction to each executing mechanism in real time by executing a control distribution algorithm. The intelligent fault detection and correction module is used for intelligently judging whether the executing mechanism generates faults or not and generating fault modes by sensing the actual output control quantity of the executing mechanism in real time and comparing the actual output control quantity with the command signal, and intelligently correcting and removing the faults by correcting the real-time input of the control distribution module aiming at each fault mode so as to ensure that the working state of the system is not influenced by the faults.
The control distribution method with intelligent fault detection and correction functions disclosed by the embodiment comprises the following steps:
Step one: and constructing an integral closed-loop model of the control system, defining all parameters required in the control process, defining basic functions and control parameter definitions of all parts of the control system, and building a dynamics model and a control law of the control system.
Step 1.1: and constructing a complete control system closed-loop model formed by a virtual instruction layer and a physical system layer, and determining the physical meaning of the function and each parameter of each part.
The closed loop schematic of the control system established in this embodiment is shown in fig. 1. In the embodiment, taking spacecraft attitude control as an example, the constructed control system is an attitude control system of a spacecraft; the parameters of the spacecraft were set as follows: the rotational inertia of the spacecraft is: j=diag [ (J xx Jyy Jzz)]＝diag[(200 150 280)]kg·m2), the spacecraft is in earth orbit with orbit altitude h=1000 km.
First establish the necessary reference coordinate system: the body coordinate system of the spacecraft is defined as o bxbybzb, the origin of the body coordinate system is defined at the mass center of the spacecraft, the o bxb axis coincides with the inertia main axis of the spacecraft, the o byb axis is perpendicular to the o bxb axis and is positioned on the main symmetry plane, and the o bzb axis is determined by a right-hand rule. The orbit coordinate system of the spacecraft is defined as o bxoyozo, the origin of the orbit coordinate system is defined at the mass center of the spacecraft, the o bxo axis coincides with the speed vector of the spacecraft, the o byo axis is perpendicular to the o bxo axis and points to the earth center from the mass center of the spacecraft, and the o bzo axis is determined by a right-hand rule. The three-axis rotation speed of the spacecraft around the body coordinate system is defined as the attitude angular speed; the three axes of the body coordinate system rotate in order of o bzb-obxb-obyb to be overlapped with the orbit coordinate system, and the three angles are respectively defined as a yaw angle psi and a roll angleAnd a pitch angle θ, constituting an attitude angle of the spacecraft. The attitude angle of the spacecraft triaxial is the state quantity that needs to be controlled in this embodiment.
The gesture motion of the spacecraft is controlled by adopting 4 momentum wheels as an actuating mechanism, so that an overdrive control system is formed. The moment of inertia of each momentum wheel is defined as: i w＝0.5kg·m2. The momentum wheel is installed in the following mode: the normal directions of the three momentum wheels are parallel to the three axes of the body coordinate system o bxb、obyb、obzb and are numbered as No. 1, no. 2 and No. 3 momentum wheels, and the normal directions of the No. 4 momentum wheels form angles of 45 degrees with the plane o bxbyb and the axis o bzb; the momentum wheel assembly matrix B a can be determined as follows:
the initial attitude angle of the spacecraft is Θ 0＝30°,ψ0 =30°, the desired attitude angle isΘ d＝0°,ψd =0°. The initial angular velocity is: omega 0＝[0.1 0.1 0.1]T rad/s, the desired angular velocity is: omega d＝[0 0 0]T rad/s.
Step 1.2: and establishing a dynamic model and a control law of the control system.
The attitude dynamics of a spacecraft under gravity gradient force disturbance can be expressed in the form of differential equations as:
Wherein ω o is the orbital angular velocity of the spacecraft, h= [ h x hy hz]T is the moment of momentum of the momentum wheel set, T c＝[TcxTcy Tcz]T is the total moment of command generated by the attitude control law, and by adopting the PD control law, the total moment of command can be expressed as:
Wherein, the control parameter is defined as: k p1＝Kp2＝Kp3＝1,Kd1＝Kd2＝Kd3 =50.
Step two: and establishing a control allocation module for allocating the total control instruction to each execution mechanism in real time.
In the control distribution module, the control distribution problem is converted into a weighted least square problem, and the weighted least square problem of the control distribution is solved by adopting an active set algorithm method, so that the control distribution efficiency is improved. The implementation method of the second step is as follows:
Step 2.1: in the control allocation module, the control allocation problem is converted into a weighted least squares problem. The upper limit and the lower limit of the momentum wheel are respectively:
umax＝[50 50 50 50]N·m,umin＝[-50 -50 -50 -50]N·m。
The optimal working state of the momentum wheel is set as follows:
up＝[20 20 20 20]N·m。
the weighting matrix and the weighting parameters are respectively set as follows:
γ＝1e6。
step 2.2: the weighted least square problem of control distribution solved by an active set algorithm method is adopted, the control distribution efficiency is improved, and the instruction control quantity u d of the executing mechanism is quickly and accurately obtained and issued to each executing mechanism.
Step three: classifying the fault modes of the execution mechanism into three fault mode models of complete failure, amplitude clamping and efficiency reduction; and an intelligent fault detection and correction module is established, the actual output control quantity of the execution mechanism is perceived in real time through the intelligent fault detection and correction module and is compared with the instruction control quantity, whether the execution mechanism generates faults or not and the fault generation mode are intelligently judged, and the faults are intelligently corrected and removed according to each fault mode through the real-time input of the correction control distribution module, so that the working state of the system is not influenced by the faults.
Step 3.1: and classifying the fault modes of the execution mechanism into three fault mode models of complete failure, amplitude jamming and efficiency reduction.
At the beginning of the control mission for 10s, the momentum wheel No. 4 failed with a performance reduction in percent δ=80%; at 20s, the No. 2 momentum wheel has amplitude jamming fault, and the jamming amplitude isAt 30s, the momentum wheel No. 2 failed completely.
Step 3.2: the intelligent fault detection and correction module senses the actual output control quantity of the executing mechanism in real time and compares the actual output control quantity with the instruction signal, intelligently judges whether the executing mechanism generates faults and generates fault modes, intelligently corrects and eliminates the faults according to each fault mode through the real-time input of the correction control distribution module, and ensures that the working state of the system is not affected by the faults.
The intelligent fault detection and correction module workflow established by the present embodiment is shown in fig. 2.
In order to prove the effectiveness and practicability of the present invention, in this embodiment, a control allocation method without intelligent fault detection and correction functions is first applied to an attitude control system, and a first set of simulation examples are performed, and the obtained simulation results are shown in fig. 3 to 7.
As shown in fig. 3, after 10s from the start of the simulation, the magnitude of the torque actual output of momentum No. 4 is smaller than the magnitude of the command, and a failure of reduced efficiency occurs; the actual output torque value of the No. 2 momentum wheel is always kept at 10 N.m in 20s to 30s, which indicates that the amplitude jamming fault occurs, and the No. 2 momentum wheel does not output torque after 30s, so that the complete failure fault occurs. Because the above-mentioned faults cannot be detected and corrected effectively, the command torque values of the respective actuators have large fluctuation after the momentum wheel No. 2 and the momentum wheel No. 4 have failed.
As shown in FIG. 4, the components of the actual total output torque acting on the spacecraft along the three axes of the system generate fluctuation after the momentum wheel fails, and particularly the actual total torque component along the o byb axis of the system generates discontinuous jump when the No. 2 momentum wheel is blocked in amplitude and completely fails. As shown in fig. 5, after the momentum wheel fails, a significant error is generated between the actual output total torque and the command total torque, the maximum error amplitude along the o bxb axis exceeds 2N, the maximum error amplitude along the o byb axis exceeds 3N, and the maximum error amplitude along the o byb axis even reaches 50N. The command of the execution mechanism which cannot execute the control law correctly outputs a corresponding total control moment, and the influence on the control system is great.
As shown in fig. 6, during the control process, the three-axis angular velocity of the spacecraft generates large fluctuation and finally diverges after the momentum wheel fails, and the desired state is not reached; meanwhile, as shown in fig. 7, three attitude angles of roll, pitch and yaw of the spacecraft are also finally diverged, and the desired state is not reached. This means that the control of the attitude of the spacecraft fails due to the failure of the momentum wheel.
Next, the present embodiment adopts a control allocation method with intelligent fault detection and correction functions in the control system, and performs a second set of simulation examples, to obtain simulation results of fig. 8 to 12.
As shown in fig. 8, the momentum wheel No. 4 is a failure with reduced efficiency at 10s, the momentum wheel No. 2 is a failure with dead amplitude and complete failure at 20s and 30s respectively, unlike the previous simulation example, the command torque of the actuating mechanism of the momentum wheel No. 2 and the command torque of the actuating mechanism of the momentum wheel No. 4 generated by the control distribution module are not fluctuated after the failure, but the command is quickly adjusted and stably output; meanwhile, the instruction moment of the actuating mechanism of the momentum wheels 1 and 3 is adjusted along with the adjustment; this illustrates that the intelligent fault detection and correction module is functional.
Unlike the previous simulation example in which the actual total torque output fluctuates and jumps and an obvious error occurs between the actual total torque output and the command total torque, after the intelligent fault detection and correction function is adopted, as shown in fig. 9, the triaxial components of the actual total torque output acting on the spacecraft generate pulse values only at the moment of fault occurrence, and then change smoothly again and gradually converge; as shown in fig. 10, the triaxial components of the actual output total torque and the command total torque both generate errors in the form of pulses at the moment of occurrence of the fault, and the errors at the rest moments are all 0. The intelligent fault detection and correction module detects the existence of faults at the moment when three faults occur to the momentum wheel, and corrects the input of the control distribution module at the same time, so that the total moment of instructions is accurately redistributed, and the faults are ensured not to affect the attitude control of the system.
Unlike the above simulation example in which the angular velocity of the attitude and the three attitude angles of the spacecraft are divergent, after the intelligent fault detection and correction function is adopted, as shown in fig. 11 and 12, the angular velocity of the attitude of the three axes of the spacecraft and the three attitude angles of roll, pitch and yaw are converged to the desired state within a limited time, which means that the attitude of the spacecraft is successfully controlled even if the momentum wheel has serious faults, and proves that the control distribution method with the intelligent fault detection and correction function disclosed in the invention is effective and feasible.
While the foregoing detailed description has described the objects, aspects and advantages of the invention in further detail, it should be understood that the foregoing description is only illustrative of the invention, and is intended to cover various modifications, equivalents, alternatives, and improvements within the spirit and scope of the present invention.
Claims (6)
1. The control distribution method with intelligent fault detection and correction functions is characterized by comprising the following steps of: the control distribution module distributes the total control instruction to each executing mechanism in real time by executing a control distribution algorithm; the intelligent fault detection and correction module intelligently judges whether the execution mechanism generates faults and generates fault modes by sensing the actual output control quantity of the execution mechanism in real time and comparing the actual output control quantity with the command signal, and intelligently corrects and eliminates the faults by correcting the real-time input of the control distribution module aiming at each fault mode so as to ensure that the working state of the system is not influenced by the faults;
The control distribution method with intelligent fault detection and correction function comprises the following steps,
Step one: constructing an integral closed-loop model of the control system, defining all parameters required in the control process, defining basic functions and control parameter definitions of all parts of the control system, and building a dynamics model and a control law of the control system;
The first implementation method of the step is that,
Step 1.1: constructing a complete control system closed-loop model formed by a virtual instruction layer and a physical system layer, and determining the function of each part and the physical meaning of each parameter;
the complete control system closed loop consists of a physical system layer and a virtual instruction layer; the physical system layer refers to the physical entity of the control system and comprises an executing mechanism, a load and a platform for generating control quantity; the virtual instruction layer refers to a control algorithm carried in the electronic equipment, and mainly senses the motion state of a physical entity through a sensor to make a decision so as to generate a control instruction; the virtual instruction layer senses the motion state of the physical entity and generates a control instruction, the execution mechanism outputs corresponding control quantity to change the motion state of the physical entity, and the motion state of the physical entity is sensed by the virtual instruction layer, so that a closed-loop control system is formed;
Each actuator of the physical system layer receives a virtual actuator instruction issued by the control distribution module, the virtual actuator instruction is defined as u d, the output actual actuator control quantity is defined as u a, wherein u d and u a are expressed by m multiplied by 1-dimensional vectors, m is the number of the actuators, the ith component of the vector corresponds to the actuator with the number i, and i=1, 2 and … m; u a＝ud should be satisfied if the actuator fails, but u a≠ud is present if the actuator fails;
The installation matrix of the execution mechanism can be determined according to the installation position and the installation angle of each execution mechanism, and is defined as B a, and is an n multiplied by m dimensional matrix, wherein n is the dimension of the total control quantity of the system, the total control quantity acting on the physical system is obtained through u a and B a, and is defined as T a, and the calculation formula is as follows:
Ta＝Baua (1)
Under the action of the total control quantity, the physical system generates corresponding motion according to dynamics, namely a physical rule of motion, and the generated actual motion state is represented by x a(1×n);
After the virtual instruction layer senses the actual motion state x a of the physical system through the sensor, comparing the actual motion state x d(1×n) with the expected motion state x d(1×n) of the physical system, and when the actual motion state does not reach the expected motion state, the control law module generates a virtual total control instruction according to the designed control law, and the virtual total control instruction is represented by T c(1×n); only when the total control command T c is equal to the actual total control quantity T a acting on the physical entity in real time, i.e. the control quantity error therebetween satisfies: e T＝Tc-Ta =0, the control effect can be achieved; the functions of the control distribution module and the intelligent fault detection and correction module are to ensure that the control quantity error is quickly zeroed under the condition that an actuating mechanism fails: e T to 0;
The intelligent fault detection and correction module judges whether the execution mechanism generates faults or not by comparing the command u d obtained by each execution mechanism with the command u a actually output by each execution mechanism, determines the number of the execution mechanism with the faults and a specific fault mode, and can intelligently generate corrected command parameters according to the specific fault mode: virtual correction assembly matrix B v(n×m) and virtual compensation torque T f(1×n); the virtual total control command and the virtual compensation torque are differenced to obtain a virtual distribution torque v d(1×n), and the virtual distribution torque v d(1×n) meets the following conditions under the condition that all executing mechanisms do not generate saturation:
vd＝Tc-Tf＝Bvud (2)
v d and B v are inputs of a control distribution module, and because the execution mechanism has upper and lower output limits, all control conditions cannot be guaranteed to meet the equation relation of the formula (2), the control distribution module is used for calculating the optimal u d through a control distribution algorithm so that v d-Bvud is 0, and giving an instruction to the execution mechanism;
step 1.2: establishing a control system dynamics model and a control law;
describing a control system dynamics model with differential equations, expressed as:
where a (n×n) is the state transition matrix of the system, Representing the derivative of x a with respect to time; establishing a PID control law according to a state error e x＝xd-xa of the system, wherein the PID control law is expressed as:
Wherein K p,Kd,Ki represents the proportional coefficient, the differential coefficient and the integral coefficient, respectively; the system state error is converged to 0 in a short time by the PID control law, namely: e x to 0;
Step two: a control distribution module for distributing the total control instruction to each executing mechanism in real time is established;
Step three: classifying the fault modes of the execution mechanism into three fault mode models of complete failure, amplitude clamping and efficiency reduction; and an intelligent fault detection and correction module is established, the actual output control quantity of the execution mechanism is perceived in real time through the intelligent fault detection and correction module and is compared with the instruction control quantity, whether the execution mechanism generates faults or not and the fault generation mode are intelligently judged, and the faults are intelligently corrected and removed according to each fault mode through the real-time input of the correction control distribution module, so that the working state of the system is not influenced by the faults.
2. The control distribution method with intelligent fault detection and correction function according to claim 1, characterized in that:
In the control distribution module, the control distribution problem is converted into a weighted least square problem, and the weighted least square problem of the control distribution is solved by adopting an active set algorithm method, so that the control distribution efficiency is improved; the implementation method of the second step is that,
Step 2.1: in the control distribution module, converting the control distribution problem into a weighted least square problem;
The upper and lower bounds of the actuator are defined as u max(1×m) and u min(1×m), respectively, and their ith element represents the maximum or minimum output value of the actuator numbered i, so the actuator output command generated during the control allocation must be between the upper and lower bounds, which satisfies both the constraints:
umin≤ud≤umax (5)
The actuator also has an optimal working state, which is defined as u p(1×m); the expression incorporating the weighted least squares method describes the performance index of the control allocation problem:
J＝||wu(ud-up)||2+γ||wv(Bvud-vd)||2 (6)
Wherein w u(m×m),wv(n×n) is a weighting matrix for the working condition of the executing mechanism and the control distribution efficiency, and gamma is a weighting coefficient for the control distribution; the performance index describes the degree of deviation of the expected output control quantity of the execution mechanism from the expected total control quantity and the optimal working state of the execution mechanism, and simultaneously considers two factors of the total control quantity precision and the optimal working condition, and the importance degree between the two factors is measured by introducing a weighting matrix and a coefficient; to meet the accuracy priority of the total control amount, so gamma is set as a coefficient with a large magnitude; the performance index shown in formula (6) is transformed into:
the control allocation problem is then described as:
Namely: under the condition that the upper limit and the lower limit of the output of the executing mechanism are met, the control distribution problem is converted into a weighted least square problem, so that the performance index of the weighted least square form reaches the minimum value, and the highest precision of the total control quantity is obtained;
Step 2.2: the weighted least square problem of control distribution solved by an active set algorithm method is adopted, the control distribution efficiency is improved, the instruction control quantity u d of the executing mechanism is rapidly and accurately obtained, and the instruction control quantity u d is issued to each executing mechanism;
Defining an effective set as W s(1×m), and when the execution mechanism with the number of i is used, the instruction control quantity of the execution mechanism meets the following conditions: u min(i)≤ud(i)≤umax (i), then the active set ith element satisfies: w s (i) =0; when u d(i)＝umax (i), there is W s (i) =1, when u d(i)＝umin (i), there is W s (i) = -1; the solving steps of the active set method are as follows:
Step 2.2.1: selecting an initial value The method meets the following conditions: u min≤ud 0≤umax, setting an initial active set W s 0＝[0 … 0]T (1×m), and enabling the circulation times k=0; defining a residual r=b-a uud K;
Step 2.2.2: columns of a u corresponding to non-0 elements in the active set W s K are removed from a u, resulting in a new a u *, e.g., the first element in the active set is 1, i.e., W s (1) =1, the first column a u of a u (1) is culled from a u, Columns 2 to m of A u form a new matrix, A u *＝Au (: 2:m), and the pseudo-inverse A u *+, Defining an allocation disturbance value p=A u * +R, eliminating p elements corresponding to non-0 elements in the active set W s K from p, Obtaining new p *; Computing u d opt＝ud K+p*;
Step 2.2.3: judging whether u d opt meets the following conditions: u min≤ud opt≤umax, if yes, skipping step 2.2.4, otherwise, skipping step 2.2.7;
Step 2.2.4: updating residual errors: r=r-a u * p, the lagrangian is calculated: λ=w s K·(Au T R), determine whether the lagrangian satisfies: lambda >0, i.e. each element in lambda is greater than 0, if yes, skipping step 2.2.5, otherwise skipping step 2.2.6;
Step 2.2.5: the result of the control allocation problem is found, u d＝ud opt is made, and the algorithm is ended;
Step 2.2.6: u d K+1＝ud opt is calculated, and the element in W s K corresponding to the minimum value element in lambda is changed into 0; let k=k+1, return to step 2.2.2;
Step 2.2.7: defining a distance matrix:
The smallest element D min in the D matrix is defined as satisfying: u min≤ud K+αp*≤umax's minimum step size α min, calculating u d K+1＝ud K+αmin p, and changing the element in W s K corresponding to the column in which D min is located to sign (D min); let k=k+1, return to step 2.2.2;
According to the effective set algorithm, the instruction control quantity u d of the executing mechanism can be quickly and accurately obtained and issued to each executing mechanism.
3. The control distribution method with intelligent fault detection and correction function according to claim 2, characterized in that: the implementation method of the third step is that,
Step 3.1: classifying the fault modes of the execution mechanism into three fault mode models of complete failure, amplitude clamping and efficiency reduction;
the operating state of the actuator, that is, the relation between the actual control amount u a output by the actuator and the received virtual control instruction u d, may be expressed as:
ζ (1×m) is the actuator fault factor, Is the fault amplitude; when ζ=ones (1, m) andWhen the elements in zeta are all 1,When the medium elements are all 0, no actuating mechanism fails, the system works normally, and u a＝ud is satisfied;
when ζ (i) =0, When the actuating mechanism with the number i has a complete failure fault mode, namely the actuating mechanism cannot generate any control quantity output and cannot be used any more;
when ζ (i) =0, When the actuating mechanism with the number i has an amplitude clamping fault mode, namely the control quantity output by the actuating mechanism is always kept at a fixed value C and cannot be adjusted;
When zeta (i) is more than 0 and less than 1, When the executing mechanism with the number i generates a performance reduction fault mode, namely the control quantity actually output by the executing mechanism is always smaller than the command control quantity received by the executing mechanism;
Step 3.2: the intelligent fault detection and correction module senses the actual output control quantity of the executing mechanism in real time and compares the actual output control quantity with the instruction signal, intelligently judges whether the executing mechanism generates faults and generates fault modes, intelligently corrects and eliminates the faults according to each fault mode through the real-time input of the correction control distribution module, and ensures that the working state of the system is not affected by the faults;
Sequentially detecting the 1 st to the m-th execution mechanisms in each closed-loop control cycle, and firstly detecting whether the execution mechanism fails, namely whether u a(i)＝ud (i) is met; if yes, the executing mechanism has no fault, and the next executing mechanism is continuously detected; if not, the executing mechanism fails, and the failure mode is judged; firstly judging whether a complete failure fault mode is generated and correcting; if the detection of the 1 st to the m-th execution mechanisms does not occur in each closed-loop control cycle in turn, firstly detecting whether the execution mechanism fails, namely whether u a(i)＝ud (i) is met, i=1, 2 … m; if yes, the executing mechanism has no fault, and the next executing mechanism is continuously detected; if not, the executing mechanism generates a complete failure mode, and whether the amplitude jamming failure mode is generated or not is judged and corrected; if the amplitude jamming fault mode does not occur, judging that the efficiency is reduced, correcting and starting to detect the next actuating mechanism until intelligent fault detection and correction are completed on all actuating mechanisms, inputting corrected parameters into a control distribution module to distribute total control quantity, and completing single closed-loop control; and performing circulation control according to the single closed-loop control to ensure that the working state of the system is not affected by faults.
4. The control distribution method with intelligent fault detection and correction function as claimed in claim 3, wherein: the method for judging whether the complete failure fault mode is generated and correcting the complete failure fault mode is that,
When u a(i)≠ud(i),ua (i) =0 is detected, that is, the output value of the executing mechanism is not equal to the instruction value, and the output value is 0, judging that the executing mechanism has a complete failure fault mode at the moment;
When the execution mechanism generates a complete failure fault mode, the following adjustment is made on the input value of the control distribution module:
let T f＝0,vd＝Tc, and B v＝[Ba(:,1:i),0(n×1),Ba (: i+ 1:m) ];
I.e., T c as the virtual control split torque v d, all elements of the i-th column of the actual assembly matrix B a are replaced with zeros as B v, and v d and B v are input to the control split module.
5. The control distribution method with intelligent fault detection and correction function as claimed in claim 3, wherein: the method for judging whether the amplitude clamping fault mode is generated and correcting the amplitude clamping fault mode is that,
When u ai≠udi,uai(K)＝uai (K-1) =const is detected, that is, the output value of the executing mechanism is not equal to the instruction value, and the output value of the executing mechanism is equal to the constant value which is not equal to 0 in the last closed-loop control cycle, judging that the executing mechanism has an amplitude jamming fault mode at the moment;
when the executing mechanism generates an amplitude clamping fault mode, the following adjustment is made on the input value of the control distribution module:
Order the V d＝Tc-Tf, and
I.e. T c and virtual compensation momentAs virtual control distribution moment v d, replacing all elements of the ith column of the actual assembly matrix B a with zeros as B v, and v d and B v as inputs to the control distribution module.
6. The control distribution method with intelligent fault detection and correction function as claimed in claim 3, wherein: the method for judging whether the performance reduction fault mode is generated and correcting the performance reduction fault mode is that,
When u a(i)≠ud(i),0＜|uai|<|udi is detected, that is, the output value of the executing mechanism is not equal to the instruction value, and the absolute value of the output value is smaller than the absolute value of the instruction value, the executing mechanism can be judged to have the performance reduction fault mode at the moment;
when the execution mechanism generates the efficiency reduction fault mode, the following adjustment is made on the input value of the control distribution module:
Let T f＝0,vd＝Tc, and B v＝[Ba(:,1:i+1),(uai/udi)Ba(i),Ba (: i+ 1:m) ];
I.e., T c as the virtual control split torque v d, multiplying all elements of the i-th column of the actual assembly matrix B a by a factor δ= (u ai/udi), and v d and B v as inputs to the control split module.
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