Intelligent high-speed aircraft flight / push control parameter optimization method based on protopigeon grouping
Through the method based on the intelligent method of pigeon flocking, the integrated control parameters of high-speed aircraft flight/push are optimized, which solves the shortcomings in the design optimization of control parameters in the existing technology and achieves a more stable flight control effect.
Patent Information
- Application Number
- CN202411371503.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-29
- Publication Date
- 2025-02-14
AI Technical Summary
The lack of systematic research on the integrated control parameters of high-speed aircraft flight/push in the prior art has led to strong coupling of the control system and it is difficult to achieve stable flight.
Using a method based on the intelligence of the dove flocking, a high-speed aircraft flight/push integrated system model is constructed, and an improved longitudinal channel control law strategy is designed, and the control parameters are optimized using the exploration group group optimization algorithm.
The integrated control effect of high-speed aircraft flight/push is improved, the stable flight capability of the aircraft is enhanced, and efficient adjustment of control parameters is achieved.
Smart Images
Figure CN119440081A_ABST
Abstract
Description
Technical Field
[0001] The invention discloses a high-speed aircraft flight / thrust control parameter optimization method based on pigeon grouping intelligence, and belongs to the field of autonomous control of unmanned aerial vehicles. Background Art
[0002] In recent years, the research on high-speed aircraft has been continuously deepened, and more and more research has been carried out around the integration of high-speed aircraft flight / thrust, and many high-speed aircraft flight / thrust integration models have been proposed. However, the flight environment of high-speed aircraft is complex, and the design of flight / thrust integration makes the control system have strong coupling. In the past research, there has been no systematic research on the setting of high-speed aircraft flight / thrust integration control parameters. Therefore, the design optimization method of control parameters for high-speed aircraft flight / thrust integration has quite important research value. Summary of the invention
[0003] The present invention proposes a method for optimizing control parameters of high-speed aircraft flight / propulsion integration based on pigeon swarming intelligence, and its purpose is to provide a high-speed aircraft flight / propulsion integration control method and an efficient parameter setting method, aiming to improve the control effect of high-speed aircraft flight / propulsion integration and enhance the stable flight capability of high-speed aircraft.
[0004] The present invention is a method for optimizing the flight / thrust control parameters of a high-speed aircraft based on pigeon swarming intelligence, and the specific implementation steps are as follows:
[0005] Step 1: High-speed aircraft flying / pushing integrated model
[0006] Force equations for high-speed aircraft:
[0007]
[0008] Among them, V represents the flight degree, α represents the angle of attack, β represents the sideslip angle, and the above variables are used as the three states of high-speed aircraft. g represents the acceleration of gravity, D represents the aerodynamic drag, L represents the aerodynamic lift, Y represents the aerodynamic side force, and T represents the engine thrust.
[0009] The moments acting on the aircraft include pitch moment, yaw moment and roll moment. The moment equation can be expressed as follows:
[0010]
[0011] In the formula, q represents the pitch angular velocity, r represents the yaw angular velocity, and p represents the roll angular velocity. The above variables are used as the three states of the high-speed aircraft. m represents the pitch moment, n represents the yaw moment, and l represents the roll moment. I ** It represents the moment of inertia of a coordinate axis or the moment of inertia product of two axes.
[0012] Aircraft aerodynamics can be broken down into three parts:
[0013] The mathematical expression of aerodynamic lift L is as follows:
[0014]
[0015] The mathematical expression of aerodynamic side force Y is as follows:
[0016]
[0017] The mathematical expression of aerodynamic resistance D is as follows:
[0018]
[0019] Step 2: Design of the integrated longitudinal control law for high-speed aircraft flight / propulsion
[0020] Design the control law of the longitudinal channel altitude loop of a high-speed aircraft, which is controlled from the inside to the outside by pitch velocity q, pitch angle θ, and altitude h. The pitch velocity control loop tracks the pitch velocity command, and the specific control law is:
[0021]
[0022] Among them, q des is the pitch angle velocity command, which is obtained by the pitch angle control loop. The specific control law of the pitch angle control loop is:
[0023]
[0024] Among them, θ des is the pitch angle command, which is obtained by the altitude control loop. The control law of the altitude control loop is:
[0025]
[0026] θ des =γ des +α
[0027] On the basis of altitude maintenance, the longitudinal channel thrust control law is further designed to ensure thrust stability, speed stability and angle of attack stability. The speed control law is designed as:
[0028]
[0029] The control law of the angle of attack is designed as:
[0030]
[0031] The final high-speed aircraft flight / propulsion integrated longitudinal control law is as follows Figure 1a , 1b As shown. Among them, Figure 1a is the height control loop, Figure 1b It is the thrust control loop.
[0032] Step 3: Optimization of integrated control parameters of flying / pushing based on pigeon grouping intelligence
[0033] In D-dimensional space, set the number of pigeons to N and the initial position of the pigeons to X. i =[X i1 ,X i2 ,X i3 ,…,X iD ], speed is V i =[V i1 ,V i2 ,V i3 ,…,V iD ], where i = 1, 2, 3, …, N, and the position of the pigeon represents the independent variable of the fitness function to be solved, that is, the control parameter of the control system.
[0034] The parameter optimization fitness function of the control system is obtained by modifying the conventional time-weighted integration as follows:
[0035]
[0036] Among them, J is the fitness value, e(t) is the error function, which represents the error of the system at time t.
[0037] In the initialization phase, the pigeon group is divided into two sub-groups, namely the main group and the exploration group. In the first phase, each pigeon in the main group updates its position and speed according to the following formula:
[0038]
[0039] Where R represents the map and guide factor, X gbest represents the global best position of the pigeon after t-1 cycles, V i (t) represents the speed of the i-th individual at the t-th iteration, X i (t) represents the position of the i-th individual at the t-th iteration.
[0040] In the first stage, the pigeons of the exploration group search the new area and update their positions and speeds according to the following formula:
[0041]
[0042] Among them, R e represents the map factor of the exploration group, which is affected by the results of the previous iteration; X m is the average of the two best individuals in each round of iteration. e Update according to the following formula:
[0043]
[0044] Among them, R min Represents the minimum value set for the exploration group map factor, R max represents the maximum value of the exploration group map factor; p i is the fitness value of the ith individual, p max is the maximum value of the fitness value; ζ is the iteration index, which is set to 1 at the end of each iteration when the global optimal solution is updated, and is set to 0 when the global optimal solution is not updated.
[0045] The optimal individual average value X m The update formula is as follows:
[0046]
[0047] Among them, τ 1 With τ 2 represents the two individuals with the best global fitness value, X pbest (τ 1 ) and X pbest (τ 2 )) represents the historical optimal position of these two individuals.
[0048] In the second stage, the pigeons use landmark navigation and update the strategy as follows:
[0049]
[0050] Among them, N N (t) is the number of individuals in the pigeon group at the tth iteration, X center (t) is the center position of the pigeon group at the tth iteration, fitness(X i ) is the fitness value of the i-th individual. In the process of iterative optimization, the information of each individual in the pigeon group is the control parameter of the flying / pushing system. After the number of iterations reaches the maximum, the cycle ends and the optimal solution X is obtained. best , which is the optimal control parameter of the flight / propulsion integrated system.
[0051] Finally, the optimization steps of the high-speed aircraft flight / propulsion integrated control system are as follows, and the optimization flow chart is shown in Figure 2 .
[0052] S41. Complete state balancing according to the initial flight conditions of the aircraft to obtain state quantities and control quantities of the aircraft during stable flight.
[0053] S42, initialize the specific control parameters of the system, including the height control loop parameters Speed control loop parameters Angle of attack control loop parameters Ensure that the aircraft follows the control signal input process stably.
[0054] S43, divide the pigeon group into groups, calculate the adaptation value of the initial control parameters of the aircraft, and complete the initialization.
[0055] S44. After the pigeons are divided into groups, they each update their exploration map factors, and further update their speed and position.
[0056] S45. Complete the landmark operator iteration and output the optimization result.
[0057] Finally, the optimization of flight / propulsion integrated control parameters was completed. The specific results are shown in Figure 3 .
[0058] The present invention proposes a parameter optimization method based on original pigeon grouping intelligence, and its advantages and effects are: first, a flight / thrust integrated system model is constructed for high-speed aircraft, and an improved longitudinal channel control law strategy is designed for the model, and an engine mode conversion strategy is constructed. Secondly, on the basis of the pigeon group algorithm, the algorithm is improved by using the exploration group grouping. Finally, for the high-speed aircraft flight / thrust integrated system, the exploration group pigeon group optimization algorithm is used to optimize its control parameters. BRIEF DESCRIPTION OF THE DRAWINGS
[0059] Figure 1a , 1b It is the integrated flight / thrust longitudinal control law for high-speed aircraft.
[0060] Figure 2 It is a flow chart for optimizing the integrated control system of high-speed aircraft flight / propulsion.
[0061] Figure 3 It is the comparison of parameter optimization results. DETAILED DESCRIPTION
[0062] The effectiveness of the high-speed aircraft flight / thrust integrated parameter optimization method provided by the present invention is verified by a specific example below. In this example, the initial flight conditions and initial control parameters are given, and the original pigeon grouping optimization algorithm is used for optimization. The simulation environment of this example is configured with an Intel i7-9750 processor, 2.60GHz main frequency, 8G memory, and the software is MATLAB 2019b version.
[0063] A high-speed aircraft flight / thrust control parameter optimization method based on pigeon swarm intelligence is implemented as follows: Figure 2 As shown, the specific practical steps of this example are as follows:
[0064] Step 1: High-speed aircraft flying / pushing integrated model
[0065] The calculation formulas for the relevant aerodynamic parameters involved in aerodynamic force and aerodynamic torque are as follows:
[0066] C L =C L (Ma,α,δ ele )
[0067] {C Y =C Y (Ma,β,δ rud )
[0068] C D =C D (Ma,α,β,δ ele ,δ rud ,δ ail )
[0069] C m =C m (Ma,α,δ ele ,q)
[0070] {C n =C n (Ma,α,β,δ ail ,δ rud ,r,p)
[0071] C l =C l (Ma,α,β,δ ail ,δ rud ,r,p)
[0072] The specific aircraft geometric parameters, air density calculation related parameters, and aerodynamic parameters are shown in Table 1 below:
[0073]
[0074] Table 1
[0075] Step 2: Design of the integrated longitudinal control law for high-speed aircraft flight / propulsion
[0076] Aircraft control is based on a constant speed level flight state. The dynamic principle of elevator control is to change the pitch moment of the aircraft, thereby generating pitch angular velocity, and then changing the longitudinal attitude, and finally achieving the purpose of changing the flight altitude. The multi-loop altitude control of the elevator channel is in the order of the innermost loop pitch angular velocity control, the second inner loop pitch angle control, the second outer loop track angle control, and the outermost loop altitude control.
[0077] Aircraft control is based on a constant speed level flight state. The dynamic principle of thrust channel control is to change the axial force of the aircraft's longitudinal axis, thereby generating axial acceleration and ultimately achieving flight speed control. The required thrust is determined by the speed control law, and the thrust expression directly contains the throttle opening (that is, the throttle opening variable directly appears in the thrust expression and can be clearly seen), which is equivalent to directly controlling the thrust as a set value. In addition to the speed control loop, the thrust channel also contains the engine thrust control loop, which is represented by two loops.
[0078] Step 3: Optimization of integrated control parameters of flying / pushing based on pigeon grouping intelligence
[0079] Set the number of pigeons to N and the initial position of the pigeons to X i =[X i1 ,X i2 ,X i3 ,…,X iD ], speed is V i =[V i1 ,V i2 ,V i3 ,…,V iD ], where i = 1, 2, 3, ..., N, and the position of the pigeon represents the independent variable of the fitness function to be solved, that is, the control parameters of the control system, including the height control loop parameters Speed control loop parameters Angle of attack control loop parameters
[0080] In the initialization phase, the pigeon flock is divided into two sub-groups, namely the main group and the exploration group. In the first phase, each pigeon in the main group updates its position and speed, while the pigeons in the exploration group search for new areas and update their positions and speeds. In the second phase, the pigeon flock uses landmark navigation to perform updates.
[0081] After the number of iterations reaches the maximum, the loop ends and the optimal solution is obtained, which is the optimal control parameters of the flight / propulsion integrated system.
[0082] Finally, the optimization steps of the high-speed aircraft flight / thrust integrated control system are as follows.
[0083] S41. Complete state balancing according to the initial flight conditions of the aircraft to obtain state quantities and control quantities of the aircraft during stable flight.
[0084] S42. Initialize the specific control parameters of the system to ensure that the aircraft is stable in following the control signal input process.
[0085] S43, divide the pigeon group into groups, calculate the adaptation value of the initial control parameters of the aircraft, and complete the initialization.
[0086] S44. After the pigeons are divided into groups, they each update their exploration map factors, and further update their speed and position.
[0087] S45. Complete the landmark operator iteration and output the optimization result.
[0088] Finally, the optimization of flight / propulsion integrated control parameters is completed.
Claims
1. A method for optimizing high-speed aircraft flight / thrust control parameters based on pigeon swarming intelligence, characterized in that: The steps of this method are as follows: Step 1: High-speed aircraft flying / pushing integrated model Force equations for high-speed aircraft: Among them, V represents the flight degree, α represents the angle of attack, β represents the sideslip angle, and the above variables are used as the three states of the high-speed aircraft; g represents the acceleration of gravity, D represents the aerodynamic drag, L represents the aerodynamic lift, Y represents the aerodynamic side force, and T represents the engine thrust; The moments acting on the aircraft include pitch moment, yaw moment and roll moment. The moment equation is expressed as follows: Where q represents the pitch angular velocity, r represents the yaw angular velocity, and p represents the roll angular velocity. The above variables are used as the three states of the high-speed aircraft; m represents the pitch moment, n represents the yaw moment, and l represents the roll moment. I ** Indicates the moment of inertia of a coordinate axis or the moment of inertia product of two axes; Aircraft aerodynamics can be broken down into three parts: The mathematical expression of aerodynamic lift L is as follows: The mathematical expression of aerodynamic side force Y is as follows: The mathematical expression of aerodynamic resistance D is as follows: Step 2: Design of the integrated longitudinal control law for high-speed aircraft flight / propulsion Design the control law of the longitudinal channel altitude loop of the high-speed aircraft, which is controlled from the inside to the outside by the pitch velocity q, pitch angle θ, and altitude h; the pitch velocity control loop tracks the pitch velocity command, and the specific control law is: Among them, q des is the pitch angle velocity command, which is obtained by the pitch angle control loop. The specific control law of the pitch angle control loop is: Among them, θ des is the pitch angle command, which is obtained by the altitude control loop. The control law of the altitude control loop is: On the basis of altitude maintenance, the longitudinal channel thrust control law is further designed to ensure thrust stability, speed stability and angle of attack stability; the speed control law is designed as: The control law of the angle of attack is designed as: Step 3: Optimization of integrated control parameters of flying / pushing based on pigeon grouping intelligence In D-dimensional space, set the number of pigeons to N and the initial position of the pigeons to X. i =[X i1 ,X i2 ,X i3 ,…,X iD ], speed is V i =[V i1 ,V i2 ,V i3 ,…,V iD ], where i = 1, 2, 3, ..., N, and the position of the pigeon represents the independent variable of the fitness function to be solved, that is, the control parameter of the control system; The parameter optimization fitness function of the control system is obtained by modifying the conventional time-weighted integration as follows: Among them, J is the fitness value, e(t) is the error function, which represents the error of the system at time t; In the initialization phase, the pigeon group is divided into two sub-groups, namely the main group and the exploration group. In the first phase, each pigeon in the main group updates its position and speed according to the following formula: Where R represents the map and guide factor, X gbest represents the global best position of the pigeon after t-1 cycles, V i (t) represents the speed of the i-th individual at the t-th iteration, X i (t) represents the position of the i-th individual at the t-th iteration; In the first stage, the pigeons of the exploration group search the new area and update their positions and speeds according to the following formula: Among them, R e represents the map factor of the exploration group, which is affected by the results of the previous iteration; X m is the average of the two best individuals in each iteration; R e Update according to the following formula: Among them, R min Represents the minimum value set for the exploration group map factor, R max represents the maximum value of the exploration group map factor; p i is the fitness value of the ith individual, p max is the maximum value of the fitness value; ζ is the set iteration index, which is set to 1 at the end of each iteration when the global optimal solution is updated, and is set to 0 when the global optimal solution is not updated; The optimal individual average value X m The update formula is as follows: Among them, τ1 and τ2 represent the two individuals with the best global fitness value, X pbest (τ1) and X pbest (τ2)) represents the historical optimal position of these two individuals; In the second stage, the pigeons use landmark navigation and update the strategy as follows: Among them, N N (t) is the number of individuals in the pigeon group at the tth iteration, X center (t) is the center position of the pigeon group at the tth iteration, fitness(X i ) is the fitness value of the i-th individual; in the process of iterative optimization, the information of each individual in the pigeon group is the control parameter of the flying / pushing system. After the number of iterations reaches the maximum, the cycle ends and the optimal solution X is obtained. best , which is the optimal control parameter of the flight / propulsion integrated system.
2. The method according to claim 1, characterized in that: The step three further includes: the optimization step of the high-speed aircraft flight / propulsion integrated control system: S41, completing state balancing according to the initial flight conditions of the aircraft, and obtaining state quantities and control quantities of the aircraft during stable flight; S42, initialize the specific control parameters of the system, including the height control loop parameters Speed control loop parameters Angle of attack control loop parameters Ensure that the aircraft follows the control signal input process stably; S43, grouping the pigeons, calculating the adaptation values of the initial control parameters of the aircraft, and completing initialization; S44: After the pigeons are divided into groups, they update their exploration map factors and further update their speed and position. S45. Complete the landmark operator iteration and output the optimization result.