Control allocation method, system, device, medium and product for a multi-control-surface aircraft

Abstract

The application discloses a control distribution method, system, equipment, medium and product of a multi-control surface aircraft, and relates to the technical field of automatic control. The method comprises the following steps: acquiring the position of the aircraft at the current moment and a desired flight trajectory; obtaining the force and torque expected by the aircraft at the current moment based on the upper control law of the aircraft, the position of the aircraft at the current moment and the desired flight trajectory; solving the control distribution model of the position of the control surface of the aircraft by using an improved sparrow search algorithm based on the force and torque expected by the aircraft at the current moment, so as to obtain the control distribution result of the position of each control surface of the aircraft at the current moment; and adjusting the position of each control surface of the aircraft based on the control distribution result of the position of each control surface of the aircraft at the current moment, so that the aircraft can fly according to the desired flight trajectory and attitude. The application improves the control distribution efficiency of the multi-control surface aircraft, and improves the anti-interference capability.

Description

Technical Field

[0001] The present application relates to the field of automatic control technology, and in particular to a control distribution method, system, equipment, medium and product for a multi-control surface aircraft. Background Art

[0002] In recent years, with the continuous development of aircraft development technology, traditional three-channel aerodynamic layout aircraft has been unable to meet the stringent performance requirements. Modern aircraft are gradually turning to a new aerodynamic layout with multiple control surfaces to significantly improve key performance indicators such as aircraft reliability, safety and controllability. Multi-control surface aircraft usually use upper-level control rates to generate virtual control instructions. In this control law, the upper-level control system can generate the desired control instructions. However, how to effectively convert these virtual control instructions into actual control surface control instructions has become a technical problem that needs to be solved urgently. In this process, it is necessary not only to consider the synergy of multiple control surfaces, but also to ensure that each control surface responds quickly and accurately to achieve the desired flight trajectory and attitude.

[0003] Existing algorithms are used for control allocation in multi-control surface aircraft, such as the particle swarm optimization algorithm. However, these algorithms face problems such as slow convergence and easy trapping in local optimal solutions when solving complex nonlinear problems such as control allocation. There is still room for improvement in allocation efficiency and anti-interference capabilities.

[0004] Therefore, there is an urgent need for a control distribution method for a multi-control surface aircraft to solve the above problems. Summary of the Invention

[0005] The purpose of this application is to provide a control distribution method, system, equipment, medium and product for a multi-control surface aircraft, which improves the control distribution efficiency of the aircraft's control surface position and improves the anti-interference capability.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides a control allocation method for a multi-control surface aircraft, the control allocation method for a multi-control surface aircraft comprising:

[0008] Get the current position and expected flight trajectory of the aircraft;

[0009] Based on the upper-level control law of the aircraft, the aircraft's current position and the desired flight trajectory, the expected forces and torques of the aircraft at the current moment are obtained; the expected forces include: expected direct lift and expected thrust; the expected torques include: three-axis rolling torque; the upper-level control law of the aircraft includes: trajectory control, trajectory angle control, angle control, angular velocity control and speed control;

[0010] Based on the force and torque expected by the aircraft at the current moment, an improved sparrow search algorithm is used to solve the control allocation model of the aircraft control surface position to obtain the control allocation results of the positions of each control surface of the aircraft at the current moment; wherein, the control allocation model of the aircraft control surface position includes an objective function and constraints, the objective function takes the minimum value of the fitness function as the optimization goal, the fitness function is determined based on the result error of the control allocation and the energy consumed by the control surface deflection, the result error of the control allocation is the deviation between the actual force and torque and the expected force and torque, and the energy consumed by the control surface deflection is the total angle of deflection of each control surface position at the current moment compared with the position of each control surface at the previous moment; the constraints include: the deflectable position range constraint of each control surface position of the aircraft at the current moment and the difference constraint between the force and torque expected by the aircraft at the current moment and the actual force and torque; the improved sparrow search algorithm uses the tent chaotic map to initialize the positions of each control surface of the aircraft;

[0011] Based on the control allocation result of each control surface position of the aircraft at the current moment, the positions of each control surface of the aircraft are adjusted so that the aircraft flies according to the desired flight trajectory and attitude.

[0012] Optionally, the fitness function O(t) is expressed as:

[0013]

[0014] Among them, W1 and W2 are both weight matrices; f(u(t)) is the actual force and torque of the aircraft under the control surface position at time t; v(t) is the expected force and torque of the aircraft at time t calculated by the upper control law; u(t) is the position of the control surface of the aircraft at time t; u(tT) is the position of the control surface of the aircraft at time tT.

[0015] Optionally, the process of determining the deflectable position range of each control surface position of the aircraft at the current moment specifically includes:

[0016] Get the position of each control surface of the aircraft at the last moment;

[0017] Based on the position of each control surface of the aircraft at the previous moment, the deflection position limit and the deflection rate limit of each control surface of the aircraft, the deflectable position range of each control surface position of the aircraft at the current moment is determined.

[0018] Optionally, the expression for the deflectable position range of the control surface position of the aircraft at the current moment is:

[0019]

[0020] in, uis the lower limit of the deflectable position range of the aircraft control surface; T is the sampling period; ρ min is the lower limit of the deflection rate of the aircraft control surface; δ min is the lower limit of the deflection position of the aircraft control surface; is the upper limit of the deflectable position range of the aircraft control surface position; ρ max is the upper limit of the deflection rate of the aircraft control surface; δ max It is the upper limit of the deflection position of the aircraft control surface.

[0021] Optionally, the control distribution model of the aircraft control surface position is expressed as:

[0022]

[0023] Among them, J is the control distribution model of the aircraft control surface position.

[0024] Optionally, the expression of the position of each control surface of the aircraft after initialization obtained by using Tent chaotic mapping is:

[0025]

[0026] Where x represents the position of each group of control surfaces, and Γ(x) represents the combination of control surface positions after Tent chaotic mapping.

[0027] In a second aspect, the present application provides a control distribution system for a multi-control surface aircraft, wherein the control distribution system for a multi-control surface aircraft is used to implement the control distribution method for a multi-control surface aircraft, and the control distribution system for a multi-control surface aircraft includes:

[0028] A data acquisition unit, used to obtain the current position and expected flight trajectory of the aircraft;

[0029] The desired force and torque determination unit is used to obtain the desired forces and torques of the aircraft at the current moment based on the upper-level control law of the aircraft, the position of the aircraft at the current moment, and the desired flight trajectory. The desired forces include: desired direct lift and desired thrust; the desired torques include: three-axis rolling torque; the upper-level control law of the aircraft includes: trajectory control, trajectory angle control, angle control, angular velocity control, and speed control;

[0030] A control allocation result determination unit is used to solve a control allocation model for the positions of the control surfaces of the aircraft based on the forces and torques expected by the aircraft at the current moment, using an improved sparrow search algorithm, to obtain the control allocation results for the positions of the control surfaces of the aircraft at the current moment; wherein the control allocation model for the positions of the control surfaces of the aircraft includes an objective function and constraints, the objective function takes minimizing the value of a fitness function as an optimization goal, the fitness function is determined based on the result error of the control allocation and the energy consumed by the deflection of the control surfaces, the result error of the control allocation is the deviation between the actual forces and torques and the expected forces and torques, and the energy consumed by the deflection of the control surfaces is the total angle of deflection of the positions of the control surfaces at the current moment compared to the positions of the control surfaces at the previous moment; the constraints include: a deflectable position range constraint for the positions of the control surfaces of the aircraft at the current moment and a difference constraint between the forces and torques expected by the aircraft at the current moment and the actual forces and torques; the improved sparrow search algorithm uses a tent chaotic map to initialize the positions of the control surfaces of the aircraft;

[0031] The control surface position adjustment unit of the aircraft is used to adjust the positions of the control surfaces of the aircraft based on the control allocation results of the control surface positions of the aircraft at the current moment, so that the aircraft flies according to the desired flight trajectory and attitude.

[0032] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the control allocation method for a multi-control surface aircraft.

[0033] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the control allocation method for a multi-control surface aircraft.

[0034] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the control allocation method for a multi-control surface aircraft.

[0035] According to the specific embodiments provided in this application, this application has the following technical effects:

[0036] The present application discloses a control allocation method, system, equipment, medium and product for a multi-control surface aircraft. An improved sparrow algorithm is used to solve the control allocation model of the aircraft control surface positions, which significantly improves the optimization speed and the control allocation efficiency of the multi-control surface aircraft. In addition, the Tent chaotic map is introduced into the initialization stage of the population (i.e., the positions of each control surface of the aircraft), which reduces the risk of falling into a local optimal solution. Due to the non-periodicity and non-repetitiveness of the chaotic sequence, the population can cover a wider solution space, increase the chance of finding a global optimal solution, and improve the anti-interference ability. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 A schematic flow chart of a control allocation method for a multi-control surface aircraft provided in one embodiment of the present application;

[0039] Figure 2 A schematic diagram of the control system structure of a multi-control surface aircraft based on control allocation provided in one embodiment of the present application;

[0040] Figure 3 A schematic diagram of functional modules of a control distribution system for a multi-control surface aircraft provided in one embodiment of the present application;

[0041] Figure 4 A schematic diagram of the structure of a computer device provided in one embodiment of the present application.

[0042] Reference numerals:

[0043] Data acquisition unit-1, desired force and torque determination unit-2, control allocation result determination unit-3, and aircraft control surface position adjustment unit-4. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0045] The control allocation problem can be viewed as a problem of finding the inverse of a complex function. The goal is to ensure that the actual output force and torque are as close as possible to the force and torque in the virtual control command, that is, to minimize the allocation error. Combined with the position constraints of the control surfaces, this can be viewed as a process of finding the optimal solution within a specified spatial region. Therefore, the allocation error can be used as a fitness function, and an intelligent optimization algorithm can be used to iteratively search for the optimal solution.

[0046] The Sparrow Search Algorithm (SSA) is one of the more novel nature-inspired algorithms proposed in recent years. The algorithm refers to the behavior of sparrow groups in nature in foraging and escaping predators. The sparrow group is divided into three parts: finders, followers, and scouts, each responsible for different duties. Compared with traditional optimization algorithms, the Sparrow Search Algorithm has the advantages of high search accuracy, strong optimization ability, and easy implementation. However, since the randomly generated initial population is usually unevenly distributed and has low diversity, and its finder update method is relatively simple, it is easy to fall into a local optimal solution, accompanied by problems such as slow convergence speed. The technical solution of the present application overcomes the above problems.

[0047] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0048] In an exemplary embodiment, Figure 1 As shown, a control allocation method for a multi-control surface aircraft is provided, comprising the following steps S1 to S4.

[0049] Step S1: Obtain the current position and expected flight trajectory of the aircraft.

[0050] Step S2, based on the upper-level control law of the aircraft, the position of the aircraft at the current moment and the expected flight trajectory, obtain the expected forces and torques of the aircraft at the current moment; the expected forces include: expected direct lift and expected thrust; the expected torques include: three-axis rolling torque; the upper-level control law of the aircraft includes: trajectory control, trajectory angle control, angle control, angular velocity control and speed control. The three-axis rolling moment includes rolling moment, pitching moment and yaw moment; the input of trajectory control is the desired flight trajectory, and the output is the desired climb angle and yaw angle. The backstepping control law can be designed according to the kinematic equation of the aircraft; the input of trajectory angle control is the desired climb angle and yaw angle, and the output is the desired direct lift and velocity roll angle. The backstepping control law can be designed according to the translational dynamics equation of the aircraft; the input of angle control is the desired angle of attack, sideslip angle and velocity roll angle, and the output is the three-axis desired angular velocity. The backstepping control law can be designed according to the rotational kinematic equation of the aircraft; the input of angular velocity control is the three-axis desired angular velocity, and the output is the desired three-axis desired rolling moment. The backstepping control law can be designed according to the rotational dynamics equation of the aircraft; the input of speed control is the desired speed, and the output is the desired engine thrust. The backstepping control law can be designed according to the translational dynamics equation of the aircraft.

[0051] The schematic diagram of the control system structure of a multi-control surface aircraft based on control distribution is as follows Figure 2 shown.

[0052] The aircraft's current position and desired flight trajectory are input into the designed upper-level control law to obtain the desired forces and moments v(t) of the aircraft at the current moment. The desired forces and moments include: the desired rolling moment L, the desired pitching moment M, the desired yaw moment N, the desired direct lift Y, and the desired thrust T. The desired forces and moments v(t) are expressed as follows:

[0053]

[0054] Step S3: Based on the force and torque expected by the aircraft at the current moment, an improved sparrow search algorithm is used to solve the control allocation model of the aircraft control surface position to obtain the control allocation result of each control surface position of the aircraft at the current moment; wherein the control allocation model of the aircraft control surface position includes an objective function and constraints, the objective function takes the minimum fitness function value as the optimization target, the fitness function is determined based on the result error of the control allocation and the energy consumed by the control surface deflection, the result error of the control allocation is the deviation between the actual force and torque (the actual force and torque generated by each control surface position obtained by the control allocation result) and the expected force and torque, and the energy consumed by the control surface deflection is the total angle of deflection of each control surface position at the current moment compared to the control surface position at the previous moment; the constraints include: a deflectable position range constraint of each control surface position of the aircraft at the current moment and a difference constraint between the force and torque expected by the aircraft at the current moment and the actual force and torque; the improved sparrow search algorithm uses Tent chaos mapping to initialize the positions of each control surface of the aircraft.

[0055] As an optional implementation, in step S3, the fitness function O(t) is expressed as:

[0056]

[0057] Among them, W1 and W2 are both weight matrices used to balance the two performance indicators of tracking and energy consumption. Tracking refers to the result error of control allocation, and energy consumption refers to the energy consumed by control surface deflection; f(u(t)) is the actual force and torque of the aircraft at the control surface position at time t (i.e., the actual force and torque); v(t) is the expected force and torque of the aircraft at time t (i.e., the expected force and torque) calculated by the upper-level control law; u(t) is the position of the control surface of the aircraft at time t; u(tT) is the position of the control surface of the aircraft at time tT.

[0058] As an optional implementation, in step S3, the process of determining the deflectable position range of each control surface position of the aircraft at the current moment specifically includes:

[0059] Get the position of each control surface of the aircraft at the last moment.

[0060] Based on the aircraft's control surface positions at the previous moment, their deflection position limits, and their deflection rate limits, the aircraft's control surface positions at the current moment are determined. This deflection range is the optimal search space in the Sparrow algorithm.

[0061] As an optional implementation, in step S3, the deflectable position range of the control surface position of the aircraft at the current moment is expressed as:

[0062]

[0063] in, u is the lower limit of the deflectable position range of the aircraft control surface; T is the sampling period, i.e., the program simulation step length; ρ min is the lower limit of the deflection rate of the aircraft control surface; δ min is the lower limit of the deflection position of the aircraft control surface; is the upper limit of the deflectable position range of the aircraft control surface position; ρ max is the upper limit of the deflection rate of the aircraft control surface; δ max It is the upper limit of the deflection position of the aircraft control surface.

[0064] As an optional implementation, the control distribution model of the aircraft control surface position is expressed as follows:

[0065]

[0066] Among them, J is the control distribution model of the aircraft control surface position.

[0067] As an optional implementation, in step S3, the expression of the position of each control surface of the aircraft after initialization obtained by using the Tent chaotic map is:

[0068]

[0069] Where x represents the position of each group of control surfaces, and Γ(x) represents the combination of control surface positions after Tent chaotic mapping.

[0070] Specifically, the control allocation model of the aircraft control surface positions is solved using the improved sparrow search algorithm to obtain the control allocation results of the control surface positions of the aircraft at the current moment, which specifically includes the following steps:

[0071] In step S301, a population is randomly generated in the optimization space. Each individual in the population represents a control surface position deflection combination. The population is then initialized using the Tent chaotic map. The fitness function value of each individual is then calculated. Finally, the population is sorted from largest to smallest according to the fitness function value. The lower the fitness function value, the better. Before iterative optimization, the parameters related to the sparrow algorithm are set, including the population size and the maximum number of iterations. Here, the population size can be set to 80 and the maximum number of iterations to 40. Then, the population is initialized using formula (5).

[0072] The expression for randomly generating a population is:

[0073] X=lb+rand*(ub-lb)(6)

[0074] Where X represents the matrix composed of multiple sets of control surface positions, ub is the upper position boundary of the aircraft control surface, that is, ub corresponds to the upper limit of the aircraft control surface lb is the lower position boundary of the aircraft control surface, that is, lb corresponds to the lower limit of the aircraft control surface u ; rand is a matrix composed of random numbers.

[0075] In step S302, the population is divided into explorers and followers, and some individuals are randomly selected as scouts. In each iteration, the positions of the individuals (i.e., the positions of the aircraft's control surfaces) are updated according to the corresponding update formula. The formula for updating the explorer position is as follows:

[0076]

[0077] in, is the control surface position of the i-th individual in the t+1-th iteration; is the position of the control surface of the i-th individual in the t-th iteration; α is a random number in [0,1]; iter max is the maximum number of iterations; R2 is the safety value, which is a random number in [0,1]; ST is the warning value, which is a constant in [0.5,1]; Q is a random number that obeys the normal distribution.

[0078] When R2<ST, the sparrow conducts a global search for food; when R2<ST, the sparrow performs a random walk with a normal distribution.

[0079] The formula for follower position update is as follows:

[0080]

[0081] in, The worst set of control surface positions at iteration t; n is the number of participants; The control surface position of the current optimal explorer; A is a 1×d matrix, the elements of which are randomly assigned 1 or -1; A + =A T (AA T ) -1 .

[0082] When i>n / 2, individuals with lower fitness values ​​do not obtain food and therefore need to obtain more food; in other cases, individuals randomly search for a set of control surface positions near the current optimal control surface position.

[0083] The formula for reconnaissance and early warning is as follows:

[0084]

[0085] in, The optimal control surface position combination in the tth iteration; β is a random number that follows a normal distribution with a mean of 0 and a variance of 1; f i is the fitness value of the current individual, f g is the current maximum fitness value, K is a random number between -1, 1, the positive and negative numbers represent the moving direction of the sparrow, and the size represents the step length control parameter; f w is the current minimum fitness value; ε is a very small constant close to 0.

[0086] When f i ≠f g When f i =f g When , the individual is in a dangerous position, far away from the control surface position corresponding to the worst individual.

[0087] In step S303, after each individual position is updated, position constraints are applied based on the deflectable range of the aircraft's control surfaces at the current moment. After each iteration, a check is performed to determine whether the maximum number of iterations has been reached. If not, the iteration process continues with step 5. If so, the iteration ends and the optimization results are saved. The optimization results include each individual position and the corresponding fitness function value.

[0088] Step S4: Based on the control allocation result of the control surface positions of the aircraft at the current moment, the positions of the control surfaces of the aircraft are adjusted so that the aircraft flies according to the desired flight trajectory and attitude.

[0089] Specifically, the individual positions in the improved sparrow search algorithm are used as the positions of the control surfaces of the aircraft at the current moment and output, the positions of the current control surfaces of the aircraft are adjusted, and then the process returns to step S2 to continue the control allocation of the multi-control surface aircraft.

[0090] Beneficial effects of this application:

[0091] 1. This application adopts an improved chaotic sparrow search algorithm to find the solution of control allocation, which improves the optimization performance and significantly increases the optimization speed.

[0092] 2. This application introduces the Tent chaotic map into the population initialization stage, making the initial solution distribution of the population wider and reducing the risk of falling into the local optimal solution. Due to the non-periodicity and non-repetitiveness of the chaotic sequence, the population can cover a wider solution space and increase the chance of finding the global optimal solution.

[0093] Based on the same inventive concept, embodiments of the present application also provide a control distribution system for a multi-control surface aircraft for implementing the aforementioned control distribution method for a multi-control surface aircraft. The solution provided by this system is similar to the solution described in the aforementioned method. Therefore, the specific limitations of the following embodiments of the control distribution system for one or more multi-control surface aircraft can be found in the aforementioned limitations of the control distribution method for a multi-control surface aircraft, and will not be further elaborated here.

[0094] In an exemplary embodiment, Figure 3 As shown, a control distribution system for a multi-control surface aircraft is provided, comprising:

[0095] The data acquisition unit 1 is used to obtain the current position and expected flight trajectory of the aircraft.

[0096] The expected force and torque determination unit 2 is used to obtain the expected force and torque of the aircraft at the current moment based on the upper-level control law of the aircraft, the position of the aircraft at the current moment and the expected flight trajectory; the expected force includes: expected direct lift and expected thrust; the expected torque includes: three-axis rolling torque; the upper-level control law of the aircraft includes: trajectory control, trajectory angle control, angle control, angular velocity control and speed control.

[0097] The control allocation result determination unit 3 is used to solve the control allocation model of the aircraft control surface positions based on the forces and torques expected by the aircraft at the current moment, using an improved sparrow search algorithm, to obtain the control allocation results of the positions of each control surface of the aircraft at the current moment; wherein, the improved sparrow search algorithm uses a tent chaotic map to initialize the positions of each control surface of the aircraft; the control allocation model of the aircraft control surface positions includes an objective function and constraints, wherein the objective function takes the minimum value of a fitness function as an optimization goal, and the fitness function is determined based on the result error of the control allocation and the energy consumed by the control surface deflection, the result error of the control allocation is the deviation between the actual force and torque and the expected force and torque, and the energy consumed by the control surface deflection is the total angle of deflection of each control surface position at the current moment compared to the previous moment; the constraints include: a deflectable position range constraint of each control surface position of the aircraft at the current moment and a difference constraint between the expected force and torque of the aircraft at the current moment and the actual force and torque.

[0098] The control surface position adjustment unit 4 of the aircraft is used to adjust the positions of the control surfaces of the aircraft based on the control allocation results of the control surface positions of the aircraft at the current moment, so that the aircraft flies according to the desired flight trajectory and attitude.

[0099] In an exemplary embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a control distribution method for a multi-control surface aircraft.

[0100] In an exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, a control distribution method for a multi-control surface aircraft is implemented.

[0101] In an exemplary embodiment, a computer program product is provided, including a computer program, which implements a control distribution method for a multi-control surface aircraft when executed by a processor.

[0102] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a control distribution method for a multi-control surface aircraft is implemented.

[0103] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0104] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0105] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0106] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0107] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0108] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A control distribution method for a multi-control surface aircraft, characterized in that: The control distribution method for a multi-control surface aircraft comprises: Get the current position and expected flight trajectory of the aircraft; Based on the upper-level control law of the aircraft, the aircraft's current position and the desired flight trajectory, the expected forces and torques of the aircraft at the current moment are obtained; the expected forces include: expected direct lift and expected thrust; the expected torques include: three-axis rolling torque; the upper-level control law of the aircraft includes: trajectory control, trajectory angle control, angle control, angular velocity control and speed control; Based on the force and torque expected by the aircraft at the current moment, an improved sparrow search algorithm is used to solve the control allocation model of the aircraft control surface position to obtain the control allocation results of the positions of each control surface of the aircraft at the current moment; wherein, the control allocation model of the aircraft control surface position includes an objective function and constraints, the objective function takes the minimum value of the fitness function as the optimization goal, the fitness function is determined based on the result error of the control allocation and the energy consumed by the control surface deflection, the result error of the control allocation is the deviation between the actual force and torque and the expected force and torque, and the energy consumed by the control surface deflection is the total angle of deflection of each control surface position at the current moment compared with the position of each control surface at the previous moment; the constraints include: the deflectable position range constraint of each control surface position of the aircraft at the current moment and the difference constraint between the force and torque expected by the aircraft at the current moment and the actual force and torque; the improved sparrow search algorithm uses the tent chaotic map to initialize the positions of each control surface of the aircraft; Based on the control allocation result of each control surface position of the aircraft at the current moment, the positions of each control surface of the aircraft are adjusted so that the aircraft flies according to the desired flight trajectory and attitude.

2. The control distribution method for a multi-control surface aircraft according to claim 1, characterized in that: The expression of fitness function O(t) is: Among them, W1 and W2 are both weight matrices; f(u(t)) is the actual force and torque of the aircraft under the control surface position at time t; v(t) is the expected force and torque of the aircraft at time t calculated by the upper control law; u(t) is the position of the control surface of the aircraft at time t; u(tT) is the position of the control surface of the aircraft at time tT.

3. The control distribution method for a multi-control surface aircraft according to claim 2, characterized in that: The process of determining the deflectable position range of each control surface position of the aircraft at the current moment specifically includes: Get the position of each control surface of the aircraft at the last moment; Based on the position of each control surface of the aircraft at the previous moment, the deflection position limit and the deflection rate limit of each control surface of the aircraft, the deflectable position range of each control surface position of the aircraft at the current moment is determined.

4. The control distribution method for a multi-control surface aircraft according to claim 3, characterized in that: The expression of the deflectable position range of the aircraft's control surface position at the current moment is: in, is the lower limit of the deflectable position range of the aircraft control surface; T is the sampling period; ρ min is the lower limit of the deflection rate of the aircraft control surface; δ min is the lower limit of the deflection position of the aircraft control surface; is the upper limit of the deflectable position range of the aircraft control surface position; ρ max is the upper limit of the deflection rate of the aircraft control surface; δ max It is the upper limit of the deflection position of the aircraft control surface.

5. The control distribution method for a multi-control surface aircraft according to claim 4, characterized in that: The expression of the control distribution model of the aircraft control surface position is: Among them, J is the control distribution model of the aircraft control surface position.

6. The control distribution method for a multi-control surface aircraft according to claim 1, characterized in that: The expression of the position of each control surface of the aircraft after initialization obtained by using Tent chaotic mapping is: Where x represents the position of each group of control surfaces, and Γ(x) represents the combination of control surface positions after Tent chaotic mapping.

7. A control distribution system for a multi-control surface aircraft, characterized in that: The control distribution system for a multi-control surface aircraft is used to implement a control distribution method for a multi-control surface aircraft according to any one of claims 1 to 6, and the control distribution system for a multi-control surface aircraft includes: A data acquisition unit, used to obtain the current position and expected flight trajectory of the aircraft; The desired force and torque determination unit is used to obtain the desired forces and torques of the aircraft at the current moment based on the upper-level control law of the aircraft, the position of the aircraft at the current moment, and the desired flight trajectory. The desired forces include: desired direct lift and desired thrust; the desired torques include: three-axis rolling torque; the upper-level control law of the aircraft includes: trajectory control, trajectory angle control, angle control, angular velocity control, and speed control; A control allocation result determination unit is used to solve a control allocation model for the positions of the control surfaces of the aircraft based on the forces and torques expected by the aircraft at the current moment, using an improved sparrow search algorithm, to obtain the control allocation results for the positions of the control surfaces of the aircraft at the current moment; wherein the control allocation model for the positions of the control surfaces of the aircraft includes an objective function and constraints, the objective function takes minimizing the value of a fitness function as an optimization goal, the fitness function is determined based on the result error of the control allocation and the energy consumed by the deflection of the control surfaces, the result error of the control allocation is the deviation between the actual forces and torques and the expected forces and torques, and the energy consumed by the deflection of the control surfaces is the total angle of deflection of the positions of the control surfaces at the current moment compared to the positions of the control surfaces at the previous moment; the constraints include: a deflectable position range constraint for the positions of the control surfaces of the aircraft at the current moment and a difference constraint between the forces and torques expected by the aircraft at the current moment and the actual forces and torques; the improved sparrow search algorithm uses a tent chaotic map to initialize the positions of the control surfaces of the aircraft; The control surface position adjustment unit of the aircraft is used to adjust the positions of the control surfaces of the aircraft based on the control allocation results of the control surface positions of the aircraft at the current moment, so that the aircraft flies according to the desired flight trajectory and attitude.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the control distribution method for a multi-control surface aircraft according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the control distribution method for a multi-control surface aircraft according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the control distribution method for a multi-control surface aircraft according to any one of claims 1 to 6 is implemented.

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