CN118295445B - A fault-tolerant control method for a quadrotor drone considering multi-point power degradation and the drone - Google Patents

Abstract

The invention relates to the technical field of attitude control of a four-rotor unmanned aerial vehicle, in particular to a fault-tolerant control method of the four-rotor unmanned aerial vehicle considering power multipoint degradation. According to the invention, the problem of instability of the flight attitude of the unmanned aerial vehicle caused by power multipoint degradation is considered, the flight attitude can be effectively adjusted on the premise of not increasing hardware by establishing a physical model between the health state of the rotor wing and the dynamic response of the system and actively adjusting the power output combination of the rotor wing to realize the fault-tolerant measures, and the stable landing of the unmanned aerial vehicle is ensured. The invention makes up the defect that the existing passive fault tolerance method does not consider the fault scene of multi-point degradation, avoids the increase of volume and weight caused by hardware redundancy, and has remarkable effect on improving the flight safety of the unmanned aerial vehicle.

Description

A fault-tolerant control method for a quadrotor drone considering multi-point power degradation and a drone

Technical Field

The present invention relates to the technical field of attitude control of a quad-rotor unmanned aerial vehicle, and in particular to a quad-rotor unmanned aerial vehicle fault-tolerant control method and a UAV taking into account multi-point power degradation.

Background Art

A quad-rotor drone is an unmanned aerial vehicle that uses four motors as power sources and generates lift and thrust by rotating propellers to achieve flight. It has the advantages of light weight, small size, and high maneuverability, and is widely used in aerial photography, surveys, rescue, and other fields. The quad-rotor drone itself is an under-actuated system with the characteristics of multivariables, strong coupling, nonlinearity, and susceptibility to external disturbances. Its position and attitude have a strong coupling relationship. During the flight, due to the high-speed rotation of the actuator, the probability of its failure increases, so fault-tolerant control of actuator failures is required.

For example, the Chinese invention patent application (publication number: CN115327906A, publication date: 2022-11-11) discloses a design method and system for a fault-tolerant controller for a quad-rotor UAV. The method includes constructing a target motion model for reflecting the flight condition of the UAV by combining the fault distribution and the rotor speed of the UAV while considering the impact of the fault on the rotor; setting a relative threshold and a fixed threshold that change synchronously with the control input of the model; adjusting the control input of the model through the relative threshold and the fixed threshold in combination with the event triggering characteristics so that the flight trajectory of the UAV approaches the preset target flight trajectory; during the adjustment process, the backstepping method is used to recursively design the corresponding virtual control law and the actual control law so that the model approaches asymptotic stability.

The Chinese invention patent application (publication number: CN116719226A, publication date: 2023-09-08) discloses a disturbance suppression fault-tolerant control method for a quadrotor drone under unknown external interference, including: modeling the quadrotor drone to obtain a state space expression of the quadrotor drone model; designing four PI controllers based on the reference input signal characteristics of the quadrotor drone, tracking the input signal characteristics through the four PI controllers, and outputting a reference quantity; constructing four EID disturbance compensators based on the equivalent input interference method according to the characteristics contained in the state space expression of the quadrotor drone model, inputting the reference quantity into the four EID disturbance compensators, and suppressing the overall disturbance of the quadrotor drone through the four EID disturbance compensators.

The present invention is aimed at the situation that in the actual flight of a quad-rotor UAV, as the use time of the motor bearing increases, collisions, environmental factors and other factors are very likely to cause multiple motor degradation, affecting the flight safety of the UAV. Therefore, accurately analyzing the dynamic response of the UAV under multi-point degradation of the rotor and carrying out fault-tolerant design based on this is a key issue that must be faced in the design of the UAV. At present, the fault-tolerant design for UAVs is mainly a hardware redundancy design carried out under single-point rotor failure. Although this method can improve the fault tolerance of the UAV, it also significantly increases the cost and weight of the UAV. In addition, this method lacks a quantitative description of multi-point degradation, and does not give the impact of rotor degradation on the system dynamic response from the failure mechanism. Therefore, it is impossible to directly control the flight attitude of the system through the existing structure to ensure the flight safety of the UAV.

Summary of the invention

In order to solve the above-mentioned technical problems, the purpose of the present invention is to provide a fault-tolerant control method for a quad-rotor UAV taking into account multi-point power degradation. The method determines the optimal thrust combination for maintaining a stable flight attitude by real-time and autonomously adjusting the thrust output of the remaining power units, thereby solving the problem that the UAV's flight attitude is abnormal or even unable to meet flight requirements due to thrust degradation of multiple power rotors, and realizing UAV attitude adjustment and smooth landing.

In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions:

A fault-tolerant control method for a quadrotor drone considering multi-point power degradation, the method comprising the following steps:

S1: Read the rotor degradation status and set the health coefficient of a single rotor And the maximum thrust T _max , and use this to construct the health status matrix of the four rotors ;

S2: Substitute the rotor health state matrix to construct a quadrotor UAV system dynamics model considering power degradation;

S3: Set the fault-tolerant control intervention time t ₁ after degradation occurs, calculate the dynamic response X _deg ( t ₁ ) of the UAV after being affected by the power multi-point degradation for t ₁ time, and use it as the initial state of the fault-tolerant control;

S4: Extract the root mean square value of displacement in the three directions of X, Y, and Z , and the RMSE value under weighted average is calculated to evaluate the state of the quadrotor drone after the duration of t ₁ ;

S5: Define the thrust increment , from the current controllable thrust range of the four rotors Select the respective thrust vector , take one element from each of the four rotor thrust vectors to form a thrust candidate combination, and enumerate to form a thrust candidate set ;

S6: Define the time increment for each control adjustment , substitute each combination in the thrust candidate set into the system dynamics model constructed in step S2, and calculate the control experience of the UAV under different thrust candidate combinations Dynamic response after time , search for the thrust combination with the smallest RMSE value among the candidate combinations as the thrust combination for this time period Optimal thrust combination within

S7: Recording Experience The system dynamic response after , as the next stage of control adjustment time The initial state of the dynamic model solution is obtained, and step S6 is re-entered until the UAV resumes stable operation or lands safely.

As a further improvement, the dynamic model of the quadrotor drone system considering power degradation in step S2 is expressed as:

Where:

is the displacement of the quadrotor drone in the X, Y, and Z directions;

is the speed of the quadrotor drone in the X, Y, and Z directions;

is the unit vector of the initial body coordinates;

is the body angular velocity vector;

g is the acceleration due to gravity;

m is the mass of the drone;

_Reb is the rotation matrix from body coordinates to ground coordinates;

is the thrust coefficient, is the reaction torque coefficient;

d _i is the distance from the i -th rotor to the center of gravity of the fuselage;

is the thrust of each rotor, ;

is the body steering inertia matrix.

As a further improvement, , the matrix is as follows:

;

in, is the yaw angle, is the pitch angle, is the roll angle.

As a further improvement, the root mean square value RMS _i of the displacement in step S4 can be expressed as:

Where:

is the jth displacement of the UAV’s dynamic response in direction i;

is the mean value of the UAV’s dynamic response in the i direction,

;

n is the number of dynamic response data obtained by solving.

As a further improvement, the weighted average RMSE in step S4 is expressed as:

RMS _x , RMS _y , and RMS _z are the root mean square values of the displacements in the X, Y, and Z directions, respectively.

Furthermore, the present invention also provides a control device for a UAV, comprising: a flight data acquisition module, for acquiring flight data of a rotary-wing UAV;

Modeling module, used to build a dynamic model of a quadrotor UAV system considering power degradation;

A calculation module, used to implement steps S3-S5 in the above method to obtain an optimal thrust combination;

Adjust the module and thrust combination until the drone resumes stable operation or lands safely.

Furthermore, the present invention also provides a control system for an unmanned aerial vehicle, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing the above-mentioned method.

Furthermore, the present invention also provides a quad-rotor drone, the quad-rotor drone comprising:

One or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the drone to execute the above method.

Furthermore, the present invention also provides a computer-readable storage medium, comprising instructions, which, when executed on a drone, enable the drone to execute the above method.

The present invention adopts the above-mentioned technical solution, takes into account the problem of flight attitude instability caused by multi-point degradation of power of UAV, establishes a physical model between the health state of the rotor and the system dynamic response, and actively adjusts the rotor power output combination and other fault-tolerant measures. Without adding hardware, the flight attitude can be effectively adjusted to ensure the smooth landing of the UAV. The present invention makes up for the deficiency of the existing passive fault-tolerant method that does not consider fault scenarios such as multi-point degradation, and at the same time avoids the increase in volume and weight caused by hardware redundancy, which has a significant effect on improving the flight safety of UAVs.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of the fault-tolerant control of the present invention.

Fig. 2 Schematic diagram of thrust combination adjustment in the fault-tolerant process of UAV and its corresponding displacement in the X, Y and Z directions.

DETAILED DESCRIPTION

The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

The specific implementation steps of the present invention will be further described in detail below in conjunction with the fault-tolerant design process of a selected quad-rotor drone under two rotor degradation:

Step S1: The maximum thrust T _max of each rotor of the drone is 8.5N, and the current degradation state of the selected drone is read, that is, the health coefficients of rotors #1 and #2 are degraded to 0.8, and rotors #3 and #4 are in a healthy state. The health state matrix of these four rotors is .

Step S2: Substitute the rotor health status matrix , a dynamic model of the quadrotor UAV system considering power degradation is constructed, where the relevant structural parameters of the UAV are shown in Table 1, and the initial parameters of the UAV dynamic response are shown in Table 2.

Table 1. Relevant structural parameters of quadrotor drone

Table 2 Initial parameters of UAV dynamic response

Step S3: Set the fault-tolerant control intervention _time t1 after degradation to 0.5s, and calculate the abnormal dynamic response Xdeg (0.5) of the UAV affected by the degradation of the two rotors _for 0.5s, where the displacement responses in the X, Y, and Z directions are shown in Table 3.

Table 3 Displacement of the UAV in the X, Y, and Z directions when it is affected by multi-point degradation of power for 0.5 seconds

Step S4: extract the root mean square values of the displacements in the three directions of X, Y, and Z, which are RMS _x = 0.02, RMS _y = 0.01, and RMS _z = 0.44, respectively. The RMSE under weighted average is further obtained to be 0.16.

Step S5: Setting the thrust increment It is 1.7N, so the four rotor thrust vectors are selected as shown in Table 4. A thrust candidate combination is formed by selecting an element from each thrust column in the table, and a thrust candidate set is formed by enumeration, as shown in Table 5, with a total of 900 sets.

Table 4 Thrust vectors of the four rotors

Rotor #1 thrust Rotor #2 thrust Rotor #3 thrust Rotor #4 thrust 0N 0N 0N 0N 1.7N 1.7N 1.7N 1.7N 3.4N 3.4N 3.4N 3.4N 5.1N 5.1N 5.1N 5.1N 6.8N 6.8N 6.8N 6.8N 8.5N 8.5N

Table 5 Thrust candidate set

Step S6: Define each control adjustment time increment The time interval is 0.5s, and the dynamic response and corresponding RMSE of each combination in the thrust candidate set after 0.5s of control are calculated, as shown in Table 6. Therefore, the thrust combination corresponding to the minimum RMSE is found from the table as the optimal thrust combination in this time period, that is, {1.7N, 0N, 8.5N, 5.1N}.

Table 6 RMSE corresponding to the combination of thrust candidate sets

Step S7: The dynamic response of the optimal thrust combination after 0.5s degradation and 0.5s control is obtained. As the initial state for solving the dynamic model in the next stage, re-enter step S6 and continue to control for 5s until the drone lands smoothly. The thrust combination adjustment of the drone fault-tolerant process and its corresponding displacement in the three directions of X, Y, and Z are shown in Figure 2. In the figure, the green line is the dynamic response of the drone in the healthy state, the red line is the dynamic response of the drone under multiple control of fault-tolerant intervention every 0.5s in the rotor degradation state, and the blue line is the dynamic response of the quadrotor when it is not controlled in the fault state (used to compare the control effect). The optimal thrust combination under each optimization is recorded at the bottom, that is, the thrust value corresponding to the four rotors when the RMSE value is the smallest within a single 0.5s . It can be seen that when the two rotors are degraded, the motion response of the quadrotor in the X direction after the fault-tolerant intervention and continuous control for 5s can basically return to the healthy state, and the displacement changes in the Y and Z directions are also significantly reduced compared to those without control. Corresponding to the actual flight state of the quadrotor, there should be a small offset in the horizontal direction and a slow descent in the vertical direction. The fault-tolerant design has a good control effect on the degradation of the rotors on the same side of the two rows.

The above is a description of the embodiments of the present invention. Through the above description of the disclosed embodiments, professionals and technicians in the field can implement or use the present invention. Various modifications to these embodiments will be apparent to professionals and technicians in the field. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown in this article, but will comply with the widest range consistent with the principles and novelties disclosed herein.

Claims (8)

1. A four-rotor unmanned aerial vehicle fault-tolerant control method considering power multipoint degradation is characterized by comprising the following steps:

s1: reading the degradation state of the rotor wing, and setting the health coefficient of a single rotor wing And thrust maxima T _max, i=1, 2,3,4, and constructing therefrom a health matrix of four rotors；

S2: substituting rotor health state matrixConstructing a four-rotor unmanned aerial vehicle system dynamics model considering power degradation;

S3: setting fault-tolerant control intervention time t ₁ after degradation occurs, and calculating dynamic response X _deg(t₁ of the unmanned aerial vehicle after the unmanned aerial vehicle is affected by power multipoint degradation for t ₁ time, wherein the dynamic response X _deg(t₁ is used as an initial state of fault-tolerant control;

s4: extracting root mean square value of X, Y, Z three-direction displacement I=x, y, z; calculating an RMSE value under the weighted average to evaluate the state of the quadrotor unmanned aerial vehicle after the duration t ₁;

S5: defining thrust delta From the current controllable thrust range of four rotorsSelecting respective thrust vectorsTaking one element from each of the four rotor thrust vectors to form a thrust candidate combination, and forming a thrust candidate set by enumeration；

S6: defining each control adjustment time incrementSubstituting each combination in the thrust candidate set into the system dynamics model constructed in the step S2, and calculating dynamics response of the unmanned aerial vehicle after the control time under different thrust candidate combinationsSearching the thrust combination with the smallest RMSE value in the candidate combination as the time periodAn optimal thrust combination within;

S7: recording experiences Post system power responseAs the next stage to control the adjustment timeStep S6, the initial state of solving the lower dynamics model is re-entered until the unmanned aerial vehicle resumes steady operation or safely falls to the ground;

The dynamics model of the four-rotor unmanned aerial vehicle system considering power degradation in the step S2 is expressed as follows:

；

Wherein:

The displacement of the quadrotor unmanned aerial vehicle in the X, Y, Z direction is adopted;

is four rotor unmanned aerial vehicle in a speed in the X, Y, Z direction;

A unit vector which is an initial body coordinate;

is the angular velocity vector of the machine body;

g is gravity acceleration;

m is the mass of the unmanned aerial vehicle;

r _eb is a rotation matrix for converting the machine body coordinates into ground coordinates;

as a result of the thrust coefficient, Is a counter moment coefficient;

d _i is the distance from the ith rotor to the center of gravity of the body;

For the thrust of the respective rotor wing, ,i=1，2，3，4；

And a steering inertia matrix for the machine body.

2. The four-rotor unmanned aerial vehicle fault-tolerant control method considering power multipoint degeneration according to claim 1, wherein,The matrix is as follows:

; wherein, In order to be a yaw angle,Is used as a pitch angle of the light beam,Is the roll angle.

3. The four-rotor unmanned aerial vehicle fault-tolerant control method taking into account power multipoint degeneration according to claim 1, wherein the displacement RMS _i in step S4 is expressed as:

，i=x，y，z；

Wherein:

the j displacement amount of the dynamic response of the unmanned aerial vehicle in the i direction is obtained;

Is the mean value of the dynamic response of the unmanned aerial vehicle in the i direction,

；

N is the number of dynamic response data obtained by solution.

4. A four-rotor unmanned aerial vehicle fault-tolerant control method that takes into account power multipoint degeneration according to claim 3, wherein the RMSE of the weighted average in step S4 is expressed as:

；

RMS _x、RMS_y 、RMS_z is the root mean square value of X, Y, Z displacement in three directions, respectively.

5. A control device for an unmanned aerial vehicle, comprising:

the flight data acquisition module is used for acquiring flight data of the rotor unmanned aerial vehicle; reading the degradation state of the rotor wing, and setting the health coefficient of a single rotor wing And thrust maxima T _max, i=1, 2,3,4, and constructing therefrom a health matrix of four rotors；

The modeling module is used for constructing a four-rotor unmanned aerial vehicle system dynamics model considering dynamic degradation;

A calculation module, configured to implement steps S3-S5 in the method according to any one of claims 1-4, and obtain an optimal thrust combination;

the adjusting module is used for adjusting the thrust combination until the unmanned aerial vehicle resumes stable operation or safely falls to the ground;

the dynamic model of the four-rotor unmanned aerial vehicle system considering power degradation is expressed as follows:

；

Wherein:

The displacement of the quadrotor unmanned aerial vehicle in the X, Y, Z direction is adopted;

is four rotor unmanned aerial vehicle in a speed in the X, Y, Z direction;

A unit vector which is an initial body coordinate;

is the angular velocity vector of the machine body;

g is gravity acceleration;

m is the mass of the unmanned aerial vehicle;

r _eb is a rotation matrix for converting the machine body coordinates into ground coordinates;

as a result of the thrust coefficient, Is a counter moment coefficient;

d _i is the distance from the ith rotor to the center of gravity of the body;

For the thrust of the respective rotor wing, ,i=1，2，3，4；

And a steering inertia matrix for the machine body.

6. A control system for an unmanned aerial vehicle, comprising: one or more processors, memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for performing the method of any of claims 1-4.

7. Four rotor unmanned aerial vehicle, its characterized in that, four rotor unmanned aerial vehicle includes: one or more processors and memory; the memory is coupled with the one or more processors, the memory for storing computer program code comprising computer instructions that the one or more processors invoke to cause the drone to perform the method of any of claims 1-4.

8. A computer readable storage medium comprising instructions which, when run on a drone, cause the drone to perform the method of any one of claims 1-4.