CN109696836B - Intelligent control method for airplane steering engine electrohydraulic servo system - Google Patents

Intelligent control method for airplane steering engine electrohydraulic servo system Download PDF

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CN109696836B
CN109696836B CN201910110146.4A CN201910110146A CN109696836B CN 109696836 B CN109696836 B CN 109696836B CN 201910110146 A CN201910110146 A CN 201910110146A CN 109696836 B CN109696836 B CN 109696836B
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food source
pid controller
colony algorithm
steering engine
bee colony
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CN109696836A (en
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刘晓琳
苏杨
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Civil Aviation University of China
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B11/00—Automatic controllers
    • G05B11/01—Automatic controllers electric
    • G05B11/36—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
    • G05B11/42—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential for obtaining a characteristic which is both proportional and time-dependent, e.g. P.I., P.I.D.

Abstract

An intelligent control method for an electro-hydraulic servo system of an aircraft steering engine. The system comprises a controller consisting of an improved artificial bee colony algorithm module and a PID controller module; acquiring system error information output by a force sensor and a displacement sensor in real time by using an improved artificial bee colony algorithm module, calculating the fitness, and searching an optimal food source as the parameter output of a PID controller; and the PID controller module outputs a loading force instruction signal to the electro-hydraulic servo valve by utilizing system error information output by the force and displacement sensor and PID controller parameters output by the improved artificial bee colony algorithm module, drives the valve control hydraulic cylinder to move to generate a loading force, loads the loading force on the airplane steering engine through the buffer spring and the force sensor, and performs corresponding movement according to the loading force instruction signal. The control method effectively improves the loading precision, response speed, tracking effect and stability of the airplane steering engine electrohydraulic servo system, and realizes effective inhibition of system redundant force interference.

Description

Intelligent control method for airplane steering engine electrohydraulic servo system
Technical Field
The invention belongs to the technical field of simulation of control systems, and particularly relates to an intelligent control method for an electro-hydraulic servo system of an airplane steering engine.
Background
The electro-hydraulic servo system of the airplane steering engine is a device for loading force on the airplane steering engine so as to simulate the load condition of the airplane steering engine in the real operation process. The system can test the performance of the airplane steering engine under the laboratory condition, and compared with the traditional self-destructive experiment, the system reduces the experiment cost and shortens the experiment period. Fig. 1 is a structural schematic diagram of an electro-hydraulic servo system of a commonly used aircraft steering engine at present. As shown in FIG. 1, the electro-hydraulic servo system of the airplane steering engine comprises a controller 1, an electro-hydraulic servo valve 2, a valve-controlled hydraulic cylinder 3, a displacement sensor 4, a buffer spring 5 and a force sensor 6; wherein: the controller 1 is connected with the electro-hydraulic servo valve 2, the force sensor 6 and the displacement sensor 4; the electro-hydraulic servo valve 2 is connected with an aircraft steering engine 7 through a valve-controlled hydraulic cylinder 3 and a buffer spring 5 in sequence; the airplane steering engine 7 is simultaneously connected with the force sensor 6 and the displacement sensor 4. The working principle is as follows: the force sensor 6 and the displacement sensor 4 acquire system error information e of the airplane steering engine 7 in real time and then transmit the system error information e to the controller 1, the controller 1 calculates a loading instruction signal according to the system error information e, the valve control hydraulic cylinder 3 is driven to move by adjusting the cavity pressure of the electrohydraulic servo valve 2 to generate a loading force, the loading force is loaded onto the airplane steering engine 7 through the buffer spring 5, and the airplane steering engine 7 moves correspondingly according to the instruction signal. However, since the electro-hydraulic servo system of the aircraft steering engine is a typical passive force servo control system, the active motion of the aircraft steering engine 7 may cause an error between the output signal and the input signal of the system, and the error is an excessive force. The redundant force has the characteristics of high strength, existence at any time and continuous change along with the motion state of the airplane steering engine 7. The existence of the redundant force not only can seriously affect the control performance and the tracking effect of the system, but also has adverse effects on a plurality of important technical indexes of the system, such as loading precision, response speed, anti-interference performance and the like.
The traditional PID controller is applied to a nonlinear and time-varying airplane steering engine electrohydraulic servo system, but the self-adaptive adjustment of the controller parameters cannot be realized, and a good real-time control effect cannot be obtained. And when the PID controller adopting the artificial bee colony algorithm is used for parameter adjustment, the control performance and the tracking effect of the system are influenced because the artificial bee colony algorithm is easy to fall into local optimum and has low convergence speed.
Disclosure of Invention
In order to solve the problems, the invention aims to provide an intelligent control method of an electro-hydraulic servo system of an aircraft steering engine, which can inhibit redundant force of the electro-hydraulic servo system of the aircraft steering engine and improve the loading precision, response speed and anti-interference performance of the system.
In order to achieve the aim, the airplane steering engine electro-hydraulic servo system in the intelligent control method of the airplane steering engine electro-hydraulic servo system comprises a controller, an electro-hydraulic servo valve, a valve control hydraulic cylinder, a displacement sensor, a buffer spring and a force sensor; wherein: the controller is connected with the electro-hydraulic servo valve, the force sensor and the displacement sensor; the electro-hydraulic servo valve is connected with an airplane steering engine through a valve control hydraulic cylinder and a buffer spring in sequence; the airplane steering engine is simultaneously connected with the force sensor and the displacement sensor; the intelligent control method of the airplane steering engine electro-hydraulic servo system comprises the following steps in sequence:
1) the controller consists of an improved artificial bee colony algorithm module and a PID controller module;
2) the method comprises the steps that an improved artificial bee colony algorithm module is used for obtaining system error information e output by a force sensor and a displacement sensor in real time, fitness is calculated, a variable neighborhood search algorithm is adopted for optimizing a search mode of an artificial bee colony algorithm observation bee stage, and an optimal food source is searched and output as a PID controller parameter;
3) the PID controller module outputs a loading force instruction signal to the electro-hydraulic servo valve by using system error information e output by the force sensor and the displacement sensor and PID controller parameters output by the improved artificial bee colony algorithm module so as to drive the valve control hydraulic cylinder to move and generate a loading force, the loading force is loaded on the airplane steering engine through the buffer spring and the force sensor, and finally the airplane steering engine performs corresponding movement according to the loading force instruction signal.
In step 2), the system error information e output by the force sensor and the displacement sensor is obtained in real time by using the improved artificial bee colony algorithm module, the fitness is calculated, the search mode of the artificial bee colony algorithm observation bee stage is optimized by adopting the variable neighborhood search algorithm, and the specific working flow of searching the optimal food source as the parameter output of the PID controller is as follows:
first, the fitness function employed is:
Figure GDA0003183180910000021
where e (t) r (t) -y (t) is the error between the actual output and the desired output; ITAE denotes the absolute error in time;
then, entering an improved artificial bee colony algorithm flow; in this algorithm, the three-dimensional vector of all food sources in the population represents the PID controller parameter kp、ki、kd(ii) a In each iteration, the improved artificial bee colony algorithm compares the advantages and disadvantages of the food sources according to the fitness obtained by the formula (1), and searches for more optimal food source optimization PID controller parameters until the maximum iteration number is reached, and then the optimal PID controller parameters are obtained; the improved artificial bee colony algorithm can be divided into the following four stages:
firstly, an initialization stage: to pairMaximum neighborhood kmaxEvaluating the maximum iteration number N and the population scale SN; randomly generating an initial food source having SN solutions according to equation (2), the SN and the number of employed bees being equal; x for each food sourcei＝(xi,1,xi,2,...,xi,D) Representing that i belongs to {1, 2.,. SN }, and D is the dimension of the problem to be optimized;
xi,j＝xmin,j+rand[0,1](xmax,j-xmin,j) (2)
in the formula, xi,jRepresents the ith food source XiWherein j ∈ {1, 2.., D }; x is the number ofmax,jAnd xmin,jThe upper limit and the lower limit of the j dimension value are respectively; rand [0,1 ]]Is [0,1 ]]A random number in between;
hiring bee stage: food source X obtained at initializationiBased on the data of the data, the hiring bee generates a new food source V by solving a search equationi＝(vi,1,vi,2,...,vi,D) The search equation is solved as follows:
Figure GDA0003183180910000022
in the formula, vi,jRepresents the ith new food source ViThe j-th dimension value of (1);
Figure GDA0003183180910000023
is [ -1,1 [ ]]A random number in between; k belongs to {1, 2.,. SN } and k is not equal to i; if a new food source ViHas higher adaptability than the food source XiThen use the new food source ViReplacement food source Xi；
③ observing bee stage: feeding back food source information to the observation bees by the hiring bees, and selecting the food source by the observation bees according to the received information; for food source X when the population size is SNiLet its fitness be FiThen the probability that the food source is selected is:
Figure GDA0003183180910000031
selecting a food source XiThen, performing variable neighborhood search on the target; the variable neighborhood search process is as follows:
step 1: setting an initial feasible solution X0And a set of neighborhood structures Nk，k＝1,2,...,kmaxRecording the current optimal solution: xi←X0；k←1；
Step 2: when k is kmaxIf so, stopping the search operation; otherwise, in food source XiRandomly searching the kth neighborhood to obtain a new food source X' in the neighborhood; local search is carried out on the new food source X 'in the neighborhood to obtain the local optimal solution X' of the new food source in the neighborhood; if F (X') > F (X)i) Then Xi← X ", k ← 1; otherwise, k ← k + 1; then repeating the step 2;
fourthly, detecting bees: when the selected food source XiAfter mining, namely when the fitness is not updated to reach the preset limit, the food source is abandoned, the hiring bee at the food source is changed into a scout bee, and the next food source X is searched by adopting the formula (5)i：
xi,j＝xmin,j+rand[0,1](xmax,j-xmin,j) (5)
Record the current optimal food source XbWhen the improved artificial bee colony algorithm reaches the maximum iteration number N, stopping the operation and outputting the finally obtained optimal food source XbAs an optimal food source; otherwise, the bee-hiring stage is entered again for calculation.
In step 3), the PID controller module outputs a loading force instruction signal to the electrohydraulic servo valve by using the system error information e output by the force sensor and the displacement sensor and the PID controller parameter output by the improved artificial bee colony algorithm module to drive the valve-controlled hydraulic cylinder to move, so as to generate a loading force, the loading force is loaded to the aircraft steering engine through the buffer spring and the force sensor, and finally, the specific working flow of the aircraft steering engine performing corresponding movement according to the loading force instruction signal is as follows:
first, a PID controller parameter k is determinedp、ki、kdAnd a group of PID controller parameters are obtained by improving the artificial bee colony algorithm module; according to the group of PID controller parameters, the PID controller module outputs the deviation function e (t) of the system to a controlled object through proportional, integral and differential operations, and the control rule is as follows:
Figure GDA0003183180910000032
wherein u (t) is a loading force instruction signal output by the PID controller module;
then, the controlled objects, namely an electro-hydraulic servo valve, a valve control hydraulic cylinder, a displacement sensor and a buffer spring work according to a loading force instruction signal u (t) to obtain a system output signal y (t) and obtain a deviation function e (t) through comparison with a system input signal r (t); calculating the fitness of the group of PID controller parameters by the formula (1); at the moment, if the improved artificial bee colony algorithm reaches the maximum iteration number N, outputting the set of PID controller parameters as the optimal PID controller parameters; otherwise, calling the improved artificial bee colony algorithm again to find out the PID controller parameter corresponding to the optimal food source.
The intelligent control method of the airplane steering engine electrohydraulic servo system provided by the invention improves the search mode of the artificial bee colony algorithm in the observation bee stage by adopting the variable neighborhood search algorithm, and effectively solves the problems of low convergence speed and easy falling into local optimization of the traditional artificial bee colony algorithm. The control parameters of the PID controller are self-adaptively adjusted by adopting an improved artificial bee colony algorithm, and the problems of time variation of system parameters and serious interference of nonlinear factors are effectively solved. Therefore, on the basis of meeting the system index requirements, the loading precision, the response speed, the tracking effect and the stability of the electro-hydraulic servo system of the airplane steering engine are effectively improved, the interference on the redundant force of the system is effectively inhibited, and the system is suitable for the ground simulation experiment of the flight control system under the laboratory condition.
Drawings
Fig. 1 is a structural schematic diagram of an electro-hydraulic servo system of a commonly used aircraft steering engine at present.
FIG. 2 is a schematic structural diagram of a controller adopting the intelligent control method of the airplane steering engine electro-hydraulic servo system provided by the invention.
FIG. 3 is a flow chart of an improved artificial bee colony algorithm adopted in the intelligent control method of the airplane steering engine electro-hydraulic servo system provided by the invention.
FIG. 4 is a flow chart of the PID controller module work flow with the improved artificial bee colony algorithm in the invention.
Fig. 5(a), (b) are loading accuracy simulation curves of a PID controller using a conventional artificial bee colony algorithm and a PID controller using an improved artificial bee colony algorithm of the present invention, respectively.
Fig. 6(a), (b) are simulation curves of response speed of a PID controller using a conventional artificial bee colony algorithm and a PID controller using the improved artificial bee colony algorithm of the present invention, respectively.
Fig. 7 is a simulation curve of the excess force suppression effect of the PID controller using the conventional artificial bee colony algorithm and the PID controller using the improved artificial bee colony algorithm of the present invention.
Fig. 8 is an anti-interference simulation curve of a PID controller using a conventional artificial bee colony algorithm and a PID controller using the improved artificial bee colony algorithm of the present invention.
Detailed Description
The intelligent control method of the airplane steering engine electro-hydraulic servo system provided by the invention is described in detail below with reference to the accompanying drawings and specific embodiments.
As shown in FIG. 2, the intelligent control method of the airplane steering engine electro-hydraulic servo system provided by the invention comprises the following steps in sequence:
1) the controller 1 consists of an improved artificial bee colony algorithm module 1.1 and a PID controller module 1.2;
2) the improved artificial bee colony algorithm module 1.1 is used for acquiring system error information e output by the force sensor 6 and the displacement sensor 4 in real time, calculating the fitness, optimizing the search mode of the artificial bee colony algorithm observation bee stage by adopting a variable neighborhood search algorithm, and searching an optimal food source to be used as PID controller parameter output;
the specific working process is as follows:
firstly, aiming at the design of a fitness function in an improved artificial bee colony algorithm, considering that the time absolute error (ITAE) standard can reflect the adjustment quality of a system in the evaluation standard commonly used by the design of a controller, the ITAE is adopted for judgment. Because the optimization goal of improving the artificial bee colony algorithm is to search a food source with higher fitness and the goal of PID controller parameter optimization is to obtain the minimum value of an objective function, the fitness function adopted by the invention is as follows:
Figure GDA0003183180910000041
where e (t) r (t) -y (t) is an error between an actual output and a desired output.
And then, entering a flow of improving the artificial bee colony algorithm. In this algorithm, the three-dimensional vector of all food sources in the population represents the PID controller parameter kp、ki、kd. In each iteration, the improved artificial bee colony algorithm compares the advantages and disadvantages of the food sources according to the fitness obtained by the formula (1), and searches for better food source optimization PID controller parameters until the maximum iteration number is reached, so that the optimal PID controller parameters are obtained. The improved artificial bee colony algorithm can be divided into the following four stages, and the flow chart is shown in fig. 3.
Firstly, an initialization stage: for the maximum neighborhood kmaxAnd assigning the maximum iteration number N and the population scale SN. Randomly generating an initial food source having SN solutions according to equation (2), the SN and the number of employed bees being equal; x for each food sourcei＝(xi,1,xi,2,...,xi,D) Where i e {1, 2.,. SN }, and D is the dimension of the problem to be optimized.
xi,j＝xmin,j+rand[0,1](xmax,j-xmin,j) (2)
In the formula, xi,jRepresents the ith food source XiWherein j ∈ {1, 2.., D }; x is the number ofmax,jAnd xmin,jThe upper limit and the lower limit of the j dimension value are respectively; rand [0,1 ]]Is [0,1 ]]Random number in between.
Hiring bee stage: food source X obtained at initializationiBased on the data of the data, the hiring bee generates a new food source V by solving a search equationi＝(vi,1,vi,2,...,vi,D) The search equation is solved as follows:
Figure GDA0003183180910000051
in the formula, vi,jRepresents the ith new food source ViThe j-th dimension value of (1);
Figure GDA0003183180910000052
is [ -1,1 [ ]]A random number in between; k belongs to {1, 2.,. SN } and k is not equal to i; if a new food source ViHas higher adaptability than the food source XiThen use the new food source ViReplacement food source Xi。
③ observing bee stage: the hiring bee feeds back the food source information to the observation bee, and the observation bee selects the food source according to the received information. The invention adopts a proportional selection strategy, and the basic idea is that the probability of each individual selected to be mined in a group is proportional to the fitness of the individual. Thus, when the population size is SN, X is the food sourceiLet its fitness be FiThen the probability that the food source is selected is:
Figure GDA0003183180910000053
selecting a food source XiThen, the variable neighborhood search is carried out. The variable neighborhood search process is as follows:
step 1: setting an initial feasible solution X0And a set of neighborhood structures Nk，k＝1,2,...,kmaxRecording the current optimal solution: xi←X0；k←1。
Step 2: when k is kmaxIf so, stopping the search operation; otherwise, in food source XiTo obtain new food in the neighborhood by random search of the kth neighborhoodA source X'; local search is carried out on the new food source X 'in the neighborhood to obtain the local optimal solution X' of the new food source in the neighborhood; if F (X') > F (X)i) Then Xi← X ", k ← 1; otherwise, k ← k + 1; step 2 is then repeated.
Fourthly, detecting bees: when the selected food source XiAfter mining, namely when the fitness is not updated to reach the preset limit, the food source is abandoned, the hiring bee at the food source is changed into a scout bee, and the next food source X is searched by adopting the formula (5)i：
xi,j＝xmin,j+rand[0,1](xmax,j-xmin,j) (5)
Record the current optimal food source XbWhen the improved artificial bee colony algorithm reaches the maximum iteration number N, stopping the operation and outputting the finally obtained optimal food source XbAs an optimal food source; otherwise, the bee-hiring stage is entered again for calculation.
3) The PID controller module 1.2 outputs a loading force instruction signal to the electro-hydraulic servo valve 2 by using system error information e output by the force sensor 6 and the displacement sensor 4 and PID controller parameters output by the improved artificial bee colony algorithm module 1.1 so as to drive the valve-controlled hydraulic cylinder 3 to move, generate a loading force, and load the loading force on an airplane steering engine 7 through the buffer spring 5 and the force sensor 6, and finally the airplane steering engine 7 performs corresponding movement according to the loading force instruction signal.
The specific working process is as follows:
first, a PID controller parameter k is determinedp、ki、kdAnd a group of PID controller parameters are obtained by improving the artificial bee colony algorithm module 1.1. According to the set of PID controller parameters, the PID controller module 1.2 outputs the deviation function e (t) of the system to the controlled object through proportional, integral and differential operations, and the control rule is as follows:
Figure GDA0003183180910000061
where u (t) is the loading force command signal output by the PID controller module 1.2.
Then, the controlled objects, i.e. the electro-hydraulic servo valve 2, the valve-controlled hydraulic cylinder 3, the displacement sensor 4 and the buffer spring 5, work according to the loading force command signal u (t) to obtain a system output signal y (t) and obtain a deviation function e (t) through comparison with a system input signal r (t). And calculating the fitness of the group of PID controller parameters by the formula (1). At the moment, if the improved artificial bee colony algorithm reaches the maximum iteration number N, outputting the set of PID controller parameters as the optimal PID controller parameters; otherwise, calling the improved artificial bee colony algorithm again to find out the PID controller parameter corresponding to the optimal food source. The working flow of the PID controller module adopting the improved artificial bee colony algorithm is shown in FIG. 4.
Fig. 5(a) and (b) are simulation curves of the loading accuracy of a PID controller using a conventional artificial bee colony algorithm and a PID controller using an improved artificial bee colony algorithm of the present invention, respectively, in which curve 1 is an actual loading force and curve 2 is an instruction force. Fig. 6(a) and (b) are response speed simulation curves of a PID controller using a conventional artificial bee colony algorithm and a PID controller using an improved artificial bee colony algorithm of the present invention, respectively, and the response condition of the output end of the system is observed by inputting a step signal to the system. Fig. 7 is a simulation curve of the excess force suppression effect of the PID controller using the conventional artificial bee colony algorithm and the PID controller using the improved artificial bee colony algorithm of the present invention, in which curve 1 is the excess force generated by the system using the PID controller of the conventional artificial bee colony algorithm, and curve 2 is the excess force generated by the system using the PID controller of the improved artificial bee colony algorithm of the present invention. Fig. 8 is an anti-interference simulation curve of a PID controller adopting a conventional artificial bee colony algorithm and a PID controller adopting the improved artificial bee colony algorithm of the present invention, in which a curve 1 is an input command force, a curve 2 is an output result of the PID controller adopting the improved artificial bee colony algorithm of the present invention, and a curve 3 is an output result of the PID controller adopting the conventional artificial bee colony algorithm. Experimental results show that in an airplane steering engine electro-hydraulic servo system, compared with a PID controller adopting a traditional artificial bee colony algorithm, the PID controller adopting the improved artificial bee colony algorithm can effectively restrain redundant force, so that the system has better tracking performance.

Claims (3)

1. An intelligent control method for an electro-hydraulic servo system of an airplane steering engine comprises the steps that the electro-hydraulic servo system of the airplane steering engine comprises a controller (1), an electro-hydraulic servo valve (2), a valve control hydraulic cylinder (3), a displacement sensor (4), a buffer spring (5) and a force sensor (6); wherein: the controller (1) is connected with the electro-hydraulic servo valve (2), the force sensor (6) and the displacement sensor (4); the electro-hydraulic servo valve (2) is connected with an aircraft steering engine (7) through a valve control hydraulic cylinder (3) and a buffer spring (5) in sequence; the airplane steering engine (7) is simultaneously connected with the force sensor (6) and the displacement sensor (4); the method is characterized in that: the intelligent control method of the airplane steering engine electro-hydraulic servo system comprises the following steps in sequence:
1) the controller (1) consists of an improved artificial bee colony algorithm module (1.1) and a PID controller module (1.2);
2) the method comprises the steps that a modified artificial bee colony algorithm module (1.1) is used for obtaining system error information e output by a force sensor (6) and a displacement sensor (4) in real time, fitness is calculated, a variable neighborhood search algorithm is adopted for optimizing a search mode of an observation bee stage of the artificial bee colony algorithm, and an optimal food source is searched and output as a PID controller parameter;
3) the PID controller module (1.2) outputs a loading force instruction signal to the electro-hydraulic servo valve (2) by utilizing system error information e output by the force sensor (6) and the displacement sensor (4) and PID controller parameters output by the improved artificial bee colony algorithm module (1.1) so as to drive the valve control hydraulic cylinder (3) to move, generate a loading force, and load the loading force on an airplane steering engine (7) through the buffer spring (5) and the force sensor (6), and finally the airplane steering engine (7) performs corresponding movement according to the loading force instruction signal.
2. The intelligent control method for the electro-hydraulic servo system of the aircraft steering engine according to claim 1, wherein the method comprises the following steps: in the step 2), the system error information e output by the force sensor (6) and the displacement sensor (4) is obtained in real time by using the improved artificial bee colony algorithm module (1.1), the fitness is calculated, the search mode of the artificial bee colony algorithm observation bee stage is optimized by adopting a variable neighborhood search algorithm, and the specific working flow of searching the optimal food source as the PID controller parameter output is as follows:
first, the fitness function employed is:
Figure FDA0003183180900000011
where e (t) r (t) -y (t) is the error between the actual output and the desired output; ITAE denotes the absolute error in time;
then, entering an improved artificial bee colony algorithm flow; in this algorithm, the three-dimensional vector of all food sources in the population represents the PID controller parameter kp、ki、kd(ii) a In each iteration, the improved artificial bee colony algorithm compares the advantages and disadvantages of the food sources according to the fitness obtained by the formula (1), and searches for more optimal food source optimization PID controller parameters until the maximum iteration number is reached, and then the optimal PID controller parameters are obtained; the improved artificial bee colony algorithm can be divided into the following four stages:
firstly, an initialization stage: for the maximum neighborhood kmaxEvaluating the maximum iteration number N and the population scale SN; randomly generating an initial food source having SN solutions according to equation (2), the SN and the number of employed bees being equal; x for each food sourcei＝(xi,1,xi,2,...,xi,D) Representing that i belongs to {1, 2.,. SN }, and D is the dimension of the problem to be optimized;
xi,j＝xmin,j+rand[0,1](xmax,j-xmin,j) (2)
in the formula, xi,jRepresents the ith food source XiWherein j ∈ {1, 2.., D }; x is the number ofmax,jAnd xmin,jThe upper limit and the lower limit of the j dimension value are respectively; rand [0,1 ]]Is [0,1 ]]A random number in between;
hiring bee stage: food source X obtained at initializationiBased on the data of the data, the hiring bee generates a new food source V by solving a search equationi＝(vi,1,vi,2,...,vi,D)，Solving the search equation as follows:
Figure FDA0003183180900000021
in the formula, vi,jRepresents the ith new food source ViThe j-th dimension value of (1);
Figure FDA0003183180900000022
is [ -1,1 [ ]]A random number in between; k belongs to {1, 2.,. SN } and k is not equal to i; if a new food source ViHas higher adaptability than the food source XiThen use the new food source ViReplacement food source Xi；
③ observing bee stage: feeding back food source information to the observation bees by the hiring bees, and selecting the food source by the observation bees according to the received information; for food source X when the population size is SNiLet its fitness be FiThen the probability that the food source is selected is:
Figure FDA0003183180900000023
selecting a food source XiThen, performing variable neighborhood search on the target; the variable neighborhood search process is as follows:
step 1: setting an initial feasible solution X0And a set of neighborhood structures Nk，k＝1,2,...,kmaxRecording the current optimal solution: xi←X0；k←1；
Step 2: when k is kmaxIf so, stopping the search operation; otherwise, in food source XiRandomly searching the kth neighborhood to obtain a new food source X' in the neighborhood; local search is carried out on the new food source X 'in the neighborhood to obtain the local optimal solution X' of the new food source in the neighborhood; if F (X') > F (X)i) Then Xi← X ", k ← 1; otherwise, k ← k + 1; then repeating the step 2;
fourthly, detecting bees: when the selected food source XiAdapted after being exploitedWhen the number of non-updated times reaches the preset limit, the food source is abandoned, the hiring bee at the food source is changed into a scout bee, and the next food source X is searched by adopting the formula (5)i：
xi,j＝xmin,j+rand[0,1](xmax,j-xmin,j) (5)
Record the current optimal food source XbWhen the improved artificial bee colony algorithm reaches the maximum iteration number N, stopping the operation and outputting the finally obtained optimal food source XbAs an optimal food source; otherwise, the bee-hiring stage is entered again for calculation.
3. The intelligent control method of the electro-hydraulic servo system of the aircraft steering engine according to claim 1 or 2, which is characterized in that: in the step 3), the PID controller module (1.2) outputs a loading force instruction signal to the electro-hydraulic servo valve (2) by using the system error information e output by the force sensor (6) and the displacement sensor (4) and the PID controller parameter output by the improved artificial bee colony algorithm module (1.1) to drive the valve-controlled hydraulic cylinder (3) to move, so as to generate a loading force, the loading force is loaded to the aircraft steering engine (7) through the buffer spring (5) and the force sensor (6), and finally, the specific work flow of the aircraft steering engine (7) performing corresponding movement according to the loading force instruction signal is as follows:
first, a PID controller parameter k is determinedp、ki、kdAnd a group of PID controller parameters are obtained by improving the artificial bee colony algorithm module (1.1) to calculate; according to the group of PID controller parameters, the PID controller module (1.2) outputs the deviation function e (t) of the system to a controlled object through proportional, integral and differential operations, and the control rule is as follows:
Figure FDA0003183180900000031
wherein u (t) is a loading force instruction signal output by the PID controller module 1.2;
then, the controlled objects, namely the electro-hydraulic servo valve (2), the valve control hydraulic cylinder (3), the displacement sensor (4) and the buffer spring (5), work according to the loading force command signal u (t) to obtain a system output signal y (t) and obtain a deviation function e (t) through comparison with a system input signal r (t); calculating the fitness of the group of PID controller parameters by the formula (1); at the moment, if the improved artificial bee colony algorithm reaches the maximum iteration number N, outputting the set of PID controller parameters as the optimal PID controller parameters; otherwise, calling the improved artificial bee colony algorithm again to find out the PID controller parameter corresponding to the optimal food source.
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