CN115268261B - Improved MFAC control method based on double-water-jet propeller unmanned ship - Google Patents
Improved MFAC control method based on double-water-jet propeller unmanned ship Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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- B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
- B63H—MARINE PROPULSION OR STEERING
- B63H11/00—Marine propulsion by water jets
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- B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
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- B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
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Abstract
The invention discloses an improved MFAC control method based on a double-water-jet propeller unmanned ship, which comprises the following steps: calculating deviation e (k) according to the expected state and the current state of the unmanned ship, and calculating a pseudo partial derivative phi (k) according to the deviation and the state information of the unmanned ship; on the basis of the original model-free self-adaptive control algorithm, calculating a pseudo partial derivative phi (k); performing adaptive iterative calculation of the control quantity u (k); and then receiving a control instruction through the unmanned ship actuator, and continuously updating the unmanned ship system state until the unmanned ship system state reaches the expected state. According to the invention, through the nonlinear processing of the integral link, the self-adaptive attenuation parameter and the tanh function, the problems of slow response, convergence oscillation, steady state error and the like of the double-water-jet propeller unmanned ship system are solved, so that the unmanned ship can be stably converged to a desired state.
Description
Technical Field
The invention belongs to the field of control algorithm design, and particularly relates to an improved tight-format model-free self-adaptive control method based on a double-water-jet propeller unmanned ship.
Background
The model-free adaptive control algorithm is a control algorithm designed for a nonlinear system, and the controller design is independent of a control object model, and utilizes I/O data of a controlled system to estimate control parameters of the system on line. The algorithm is first proposed by Hou Zhongsheng professor in doctor paper in 1994, developed and perfected to date, and is widely applied to engineering, and then expanded research is carried out by multiple persons, so that a plentiful result is obtained in various fields. Based on the research on unmanned ship control of double-water-jet propellers, problems exist in engineering, the unmanned ship is more affected by uncertainty, meanwhile, the unmanned ship is different in operability at different navigational speeds, the unmanned ship is an underactuated nonlinear system, the action response is slower, the problems are all problems which need to be solved for the unmanned ship control system, and an original control algorithm cannot meet the system requirements, so that the algorithm needs to be further researched and improved in adaptability.
The publication number is CN109144066A, the name of the invention is that a PI type CFDL-MFAC algorithm is formed by introducing proportional terms on the basis of a PI type integral separation PI type tight format non-model self-adaptive course control algorithm for ships, the response speed of a system is improved, the ship course can be quickly and stably converged to a desired course, but overshoot is easy to occur to the quick response of the ship due to the system characteristic of too slow execution response of the ship, and the convergence stability caused by quick accumulation of control quantity is not considered.
The method is characterized in that a proportional control and actuating mechanism anti-saturation control algorithm is added into CFDL-MFAC, the problems of slow response, overshoot and supersaturation of an original control system are solved, the stability of the algorithm is proved, and meanwhile, the effectiveness is verified through a numerical test, but the problems of oscillation and steady state error exist.
Disclosure of Invention
The invention aims to provide an improved tight-format model-free self-adaptive control method based on a double-water-jet unmanned ship, which is designed by adding an integration link, an attenuation parameter and tanh nonlinear processing on the basis of an original algorithm, and successfully solves the problems existing in the prior art through simulation and real ship verification.
The technical solution for realizing the purpose of the invention is as follows: an improved MFAC control method based on a double water jet propeller unmanned boat, the method comprising the steps of:
Step 1, calculating deviation e (k), e (k) =y d (k) -y (k) according to an expected sailing state y d (k) and a sailing state y (k) at the moment of the current unmanned ship k;
Step 2, calculating an output control quantity u (k) based on the deviation e (k);
Step 3, an executing mechanism of the unmanned ship receives and executes a control quantity u (k) instruction, the running state of the unmanned ship is changed, and k=k+1 is set;
And 4, comparing the deviation e (k) with the expected deviation e d (k) in real time, if the deviation e (k) is smaller than the expected deviation e d (k), considering that the expected sailing state y d (k) of the unmanned ship is reached, jumping out of the cycle, ending the control process, otherwise, turning to the step 1, and continuing to circularly calculate until the deviation e (k) is smaller than the expected deviation e d (k).
Further, the calculating the output control amount u (k) based on the deviation e (k) in the step 2 specifically includes:
the unmanned ship is a multiple-input multiple-output system, expressed as:
y(k+1)＝f(y(k),…,y(k-ny),u(k),…,u(k-nu))
wherein y (k) epsilon R, u (k) epsilon R respectively represent navigation state input and control quantity output at the moment k, y (k+1) is navigation state input at the moment k+1, and n y,nu is the order of the system;
step 2-1, calculating a k-time output control amount u (k) by using the following formula:
wherein,
Δy(k)＝y(k+1)-y(k)，Δu(k-1)＝u(k)-u(k-1)，
Phi (k) =phi (1), if |phi (k) |ε or |Deltau (k-1) |ε
Wherein μ > 0 is a weight coefficient, η ε (0, 1) is a step size factor, φ (k) is a pseudo partial derivative at time k, φ (k-1) is a pseudo partial derivative at time k-1, u (k-1) is a control amount output at time k-1, λ, ρ is an adjustable control parameter, λ 1,λ2, γ is an adjustable parameter, κ is an attenuation parameter, κ ε (0, 1), T is a control calculation period, ε - =0.000001.
Step 2-2, normalizing the control quantity u (k) to beThe following conversion is performed simultaneously:
And 2-3, performing inverse normalization on the u * (k) to obtain a final output control quantity u (k).
Further, step 2 further includes:
And (3) carrying out saturation limitation on the control quantity u (k), wherein the range u (k) epsilon [ min, max ] is larger than max or smaller than min, and the control quantity is not calculated, and the max and the min are the upper limit and the lower limit of the unmanned ship actuator mechanism.
Further, step 2-3 denormalizes u * (k) based on the range u (k) ∈ [ min, max ].
Compared with the prior art, the invention has the remarkable advantages that: the unmanned ship with the double water-jet propellers is analyzed for controlling the characteristics, the effectiveness and the practicability of an improved algorithm are verified through simulation and a real ship test, and the problems of overshoot, oscillation and steady state errors of an original system are solved through adding an integral term, an attenuation parameter and a design of tanh nonlinearity to a control quantity u (k), meanwhile, the convergence stability of a control terminal is enhanced, and the unmanned ship with the double water-jet propellers has high practical value.
The invention is described in further detail below with reference to the accompanying drawings.
Drawings
Fig. 1 is a structural diagram of a controller of the present invention.
FIG. 2 is a flow chart of an improved MFAC control method based on a double water jet unmanned boat of the present invention.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
In one embodiment, in conjunction with fig. 1, an improved MFAC control method based on a twin-jet propeller unmanned boat is provided, the method comprising the steps of:
Step 1, calculating deviation e (k), e (k) =y d (k) -y (k) according to an expected sailing state y d (k) and a sailing state y (k) at the moment of the current unmanned ship k;
Step 2, calculating an output control quantity u (k) based on the deviation e (k);
Step 3, an executing mechanism of the unmanned ship receives and executes a control quantity u (k) instruction, the running state of the unmanned ship is changed, and k=k+1 is set;
And 4, comparing the deviation e (k) with the expected deviation e d (k) in real time, if the deviation e (k) is smaller than the expected deviation e d (k), considering that the expected sailing state y d (k) of the unmanned ship is reached, jumping out of the cycle, ending the control process, otherwise, turning to the step 1, and continuing to circularly calculate until the deviation e (k) is smaller than the expected deviation e d (k).
Further, in one embodiment, in conjunction with fig. 2, the calculating the output control amount u (k) based on the deviation e (k) in the step 2 specifically includes:
the unmanned ship is a multiple-input multiple-output system, expressed as:
y(k+1)＝f(y(k),…,y(k-ny),u(k),…,u(k-nu))
wherein y (k) epsilon R, u (k) epsilon R respectively represent navigation state input and control quantity output at the moment k, y (k+1) is navigation state input at the moment k+1, and n y,nu is the order of the system;
step 2-1, calculating a k-time output control amount u (k) by using the following formula:
wherein,
Δy(k)＝y(k+1)-y(k)，Δu(k-1)＝u(k)-u(k-1)，
Phi (k) =phi (1), if |phi (k) |ε or |Deltau (k-1) |ε
Wherein μ > 0 is a weight coefficient, η ε (0, 1) is a step size factor, φ (k) is a pseudo partial derivative at time k, φ (k-1) is a pseudo partial derivative at time k-1, u (k-1) is a control amount output at time k-1, λ, ρ is an adjustable control parameter, λ 1,λ2, γ is an adjustable parameter, κ is an attenuation parameter, κ ε (0, 1), T is a control calculation period, ε - =0.000001.
Here, consider the problem of systematic steady state error, add the integration link in the control quantity calculationAnd simultaneously, carrying out anti-integral saturation integral separation data processing on the data.
Here, κ is an attenuation parameter, λ 1,λ2 is an adjustable parameter, and a range κ epsilon (0, 1) is mainly used for iteratively updating, calculating and setting an attenuation limit parameter according to a control quantity u (k) output by a tight-format model-free adaptive control algorithm, so that the vibration problem caused by slow system output response and excessively fast control quantity accumulation is effectively solved, meanwhile, the system deviation factor is considered, the larger the deviation is, the larger the control quantity speed is, the convergence speed is increased, the smaller the deviation is, the control quantity speed is increased slowly, the convergence stability of the tail end of the system is ensured, and the overshoot is prevented.
And 2-2, carrying out saturation limitation on the control quantity u (k), wherein the range u (k) epsilon [ min, max ] is larger than max or smaller than min, and the control quantity is not calculated, wherein max and min are the upper limit and the lower limit of the unmanned ship actuator mechanism.
Step 2-3, normalizing the control quantity u (k) to beThe following conversion is performed simultaneously:
here, by performing the tanh nonlinear processing on the control amount, the problem of overshoot or oscillation caused by the increase of the control amount to the system can be solved.
And 2-4, performing inverse normalization on u * (k) based on the range u (k) epsilon [ min, max ], and obtaining a final output control quantity u (k).
In one embodiment, an improved MFAC control system based on a dual water jet propeller unmanned boat is provided, the system comprising, in order:
A first module for calculating a deviation e (k), e (k) =y d (k) -y (k) according to the expected voyage state y d (k) and the voyage state y (k) at the moment of the current unmanned ship k;
a second module for calculating an output control amount u (k) based on the deviation e (k);
The third module is used for controlling an execution mechanism of the unmanned aerial vehicle to receive and execute a control quantity u (k) instruction, changing the running state of the unmanned aerial vehicle, and then enabling k=k+1;
And a fourth module, configured to compare the deviation e (k) with the expected deviation e d (k) in real time, and if the deviation e (k) is smaller than the expected deviation e d (k), consider that the expected sailing state y d (k) of the unmanned ship is reached, and end control, otherwise, go to the first module to continue to perform the cyclic calculation until the deviation e (k) is smaller than the expected deviation e d (k).
Specific limitations regarding the improved MFAC control system based on the twin-jet unmanned boat may be found in the above description of the improved MFAC control method based on the twin-jet unmanned boat, and will not be described in detail herein. The various modules in the improved MFAC control system based on the double water jet propeller unmanned boat described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program:
Step 1, calculating deviation e (k), e (k) =y d (k) -y (k) according to an expected sailing state y d (k) and a sailing state y (k) at the moment of the current unmanned ship k;
Step 2, calculating an output control quantity u (k) based on the deviation e (k);
Step 3, an executing mechanism of the unmanned ship receives and executes a control quantity u (k) instruction, the running state of the unmanned ship is changed, and k=k+1 is set;
And 4, comparing the deviation e (k) with the expected deviation e d (k) in real time, if the deviation e (k) is smaller than the expected deviation e d (k), considering that the expected sailing state y d (k) of the unmanned ship is reached, jumping out of the cycle, ending the control process, otherwise, turning to the step 1, and continuing to circularly calculate until the deviation e (k) is smaller than the expected deviation e d (k).
For specific limitations on each step, reference is made to the above limitations on the improved MFAC control method based on a twin-jet propeller unmanned boat, and no further description is given here.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
Step 1, calculating deviation e (k), e (k) =y d (k) -y (k) according to an expected sailing state y d (k) and a sailing state y (k) at the moment of the current unmanned ship k;
Step 2, calculating an output control quantity u (k) based on the deviation e (k);
Step 3, an executing mechanism of the unmanned ship receives and executes a control quantity u (k) instruction, the running state of the unmanned ship is changed, and k=k+1 is set;
And 4, comparing the deviation e (k) with the expected deviation e d (k) in real time, if the deviation e (k) is smaller than the expected deviation e d (k), considering that the expected sailing state y d (k) of the unmanned ship is reached, jumping out of the cycle, ending the control process, otherwise, turning to the step 1, and continuing to circularly calculate until the deviation e (k) is smaller than the expected deviation e d (k).
For specific limitations on each step, reference is made to the above limitations on the improved MFAC control method based on a twin-jet propeller unmanned boat, and no further description is given here.
In summary, the invention analyzes the control characteristics of the unmanned ship with the double water jet propellers, pertinently improves the tight-format model-free self-adaptive control method, verifies the effectiveness and practicality of the improved algorithm through simulation and real ship tests, solves the problems of overshoot and oscillation of the original system and steady state errors by adding an integral term and an attenuation parameter to the control quantity u (k) and designing the tanh nonlinear, and shows the superiority of the improved control algorithm.
The foregoing has outlined and described the basic principles, features, and advantages of the present invention. It will be understood by those skilled in the art that the foregoing embodiments are not intended to limit the invention, and the above embodiments and descriptions are meant to be illustrative only of the principles of the invention, and that various modifications, equivalent substitutions, improvements, etc. may be made within the spirit and scope of the invention without departing from the spirit and scope of the invention.
Claims (6)
1. An improved MFAC control method based on a double water jet propeller unmanned boat, the method comprising the steps of:
Step 1, calculating deviation e (k), e (k) =y d (k) -y (k) according to an expected sailing state y d (k) and a sailing state y (k) at the moment of the current unmanned ship k;
Step 2, calculating an output control quantity u (k) based on the deviation e (k);
Step 3, an executing mechanism of the unmanned ship receives and executes a control quantity u (k) instruction, the running state of the unmanned ship is changed, and k=k+1 is set;
Step 4, comparing the deviation e (k) with the expected deviation e d (k) in real time, if the deviation e (k) is smaller than the expected deviation e d (k), considering that the expected sailing state y d (k) of the unmanned ship is reached, jumping out of the cycle, ending the control process, otherwise, turning to step 1 to continue the cycle calculation until the deviation e (k) is smaller than the expected deviation e d (k);
the calculating the output control amount u (k) based on the deviation e (k) in the step 2 specifically includes:
the unmanned ship is a multiple-input multiple-output system, expressed as:
y(k+1)＝f(y(k),L,y(k-ny),u(k),L,u(k-nu))
wherein y (k) epsilon R, u (k) epsilon R respectively represent navigation state input and control quantity output at the moment k, y (k+1) is navigation state input at the moment k+1, and n y,nu is the order of the system;
step 2-1, calculating a k-time output control amount u (k) by using the following formula:
wherein,
Δy(k)＝y(k+1)-y(k)，Δu(k-1)＝u(k)-u(k-1)，
Phi (k) =phi (1), if |phi (k) |ε or |Deltau (k-1) |ε
Wherein, mu > 0 is a weight coefficient, eta epsilon (0, 1) is a step factor, phi (k) is a k moment pseudo partial derivative, phi (k-1) is a k-1 moment pseudo partial derivative, u (k-1) is a k-1 moment output control quantity, lambda, rho is an adjustable control parameter, lambda 1,λ2, gamma is an adjustable parameter, kappa is an attenuation parameter, kappa epsilon (0, 1), T is a control calculation period, epsilon- = 0.000001;
Step 2-2, normalizing the control quantity u (k) to be The following conversion is performed simultaneously:
And 2-3, performing inverse normalization on the u * (k) to obtain a final output control quantity u (k).
2. The improved MFAC control method for a double water jet propeller-based unmanned boat of claim 1, wherein step 2 further comprises:
And (3) carrying out saturation limitation on the control quantity u (k), wherein the range u (k) epsilon [ min, max ] is larger than max or smaller than min, and the control quantity is not calculated, and the max and the min are the upper limit and the lower limit of the unmanned ship actuator mechanism.
3. The improved MFAC control method for a twin-jet propeller unmanned boat of claim 2, wherein steps 2-3 denormalise u * (k) based on the range u (k) ∈ [ min, max ].
4. An improved MFAC control system based on a double water jet unmanned boat based on the method according to any one of claims 1 to 3, characterized in that it comprises the following steps:
A first module for calculating a deviation e (k), e (k) =y d (k) -y (k) according to the expected voyage state y d (k) and the voyage state y (k) at the moment of the current unmanned ship k;
a second module for calculating an output control amount u (k) based on the deviation e (k);
The third module is used for controlling an execution mechanism of the unmanned aerial vehicle to receive and execute a control quantity u (k) instruction, changing the running state of the unmanned aerial vehicle, and then enabling k=k+1;
And a fourth module, configured to compare the deviation e (k) with the expected deviation e d (k) in real time, and if the deviation e (k) is smaller than the expected deviation e d (k), consider that the expected sailing state y d (k) of the unmanned ship is reached, and end control, otherwise, go to the first module to continue to perform the cyclic calculation until the deviation e (k) is smaller than the expected deviation e d (k).
5. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 3 when the computer program is executed by the processor.
6. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 3.
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