首页|基于离散特性的飞行器姿态智能控制方法研究及实验设计

基于离散特性的飞行器姿态智能控制方法研究及实验设计

扫码查看
针对飞行器姿态复合控制问题研究中直接力连续化处理导致的与实际工程特性差距较大问题,研究了体现直接力离散特性的控制系统构建方法及控制参数优化设计方法。首先,搭建了体现直接力离散特性的飞行器姿态复合控制系统框架及模型;然后针对复合控制问题的非线性、强耦合、多约束等复杂特性,采用PSO算法对控制律及控制分配参数进行多目标优化设计,构建了飞行器姿态智能控制系统;再通过数字仿真从控制算法、PSO算法参数、飞行器系统参数三个方面对智能控制问题研究方法进行了说明;最后,依托最新科研成果设计开发了飞行器姿态智能控制实验系统,为自动化专业本科生智能控制类课程实践教学及创新型人才培养提供了自主开放的实验研究平台。
Research and experimental design of the intelligent attitude control method for aircraft based on discrete characteristics
[Objective]Compound attitude control based on aerodynamic,thrust vector,direct force,and other manipulation structures is a hot research topic in modern aeronautics and astronautics.Additionally,improving the tracking ability of the system under high altitude and low aerodynamic efficiency is essential.To simplify the design,direct force is generally regarded as a continuous control variable in the study of compound attitude control for aircraft,which is different from the actual discrete engineering characteristics.In view of the large gap between direct force continuous processing and actual engineering characteristics,this study proposes control system construction and control parameter optimization methods based on the discrete characteristics of direct force.[Methods]First,based on the operational characteristics of each manipulation structure,a pulse modulator,which embodies the discrete characteristics of direct force,is used to construct the framework of the attitude control system.The Simulink simulation model of the compound aircraft attitude control system is constructed using MATLAB software according to the designed control system structure and the mathematical model of each link.Second,given the complex characteristics of nonlinear,strong coupling,and multiconstraints for the compound control system,the Particle Swarm Optimization(PSO)algorithm is adopted to optimize the control law and control assignment parameters based on the algorithm framework of intelligent control and intelligent distribution laws.Thus,an intelligent control system is constructed.Third,the research method for intelligent control problems is explained through digital simulation from three aspects:control algorithm,PSO algorithm parameters,and aircraft system parameters.[Results]The simulation results show that the proposed method greatly improves the control performance of the attitude-tracking problem,including steady-state error,rise time,adjustment time,and overshoot.It is obviously superior to the traditional PID control method in terms of tracking precision,speed,and security.Additionally,it is beneficial to overcome the difficulty of adjusting the control parameters caused by the change in the flight parameters.The proposed system can adapt to real-time changes in the flight environment and state,effectively exert the control efficiency of each executing agency,and improve the adaptive control ability of the system.Finally,based on the above research achievements,the experimental system for intelligent aircraft attitude control is designed and developed.This system is applied to the practical teaching of intelligent control theory and process control systems.It can also be used to strengthen students'understanding of the application and innovation of intelligent control theory in actual engineering problems from the aspects of attitude control principle,control structure design,mathematical model building,intelligent control algorithm design and implementation,and algorithm research.[Conclusions]This experimental system combines the engineering problems of aircraft attitude control with experimental teaching.By guiding students to project-based learning independently,it stimulates their interest in learning,effectively improves their ability to combine theory with practice,helps them to master scientific research methods,and cultivates and promotes students'practical and innovative abilities.In this way,an independent and open experimental research platform for the practical teaching of intelligent control courses and the cultivation of innovative talents is provided.

aircraft attitudeintelligent controldiscrete characteristicsPSO algorithmexperimental system

万春秋、李擎、崔家瑞、杨旭、李希胜

展开 >

北京科技大学 自动化学院,北京 100083

飞行器姿态 智能控制 离散特性 PSO算法 实验系统

国家自然科学基金教育部产学合作协同育人新工科建设项目教育部产学合作协同育人新工科建设项目教育部产学合作协同育人新工科建设项目北京科技大学教育教学改革与研究重点项目北京科技大学教育教学改革与研究重点项目中央高校基本科研业务费专项中国学位与研究生教育学会研究课题(2020)北京科技大学来华留学发展项目

62273033202101046001202101320001202002309017JG2021ZD02JG2019Z04FRF-TP-20-014A12020MSA1172023LHFZ07

2024

实验技术与管理
清华大学

实验技术与管理

CSTPCD北大核心
影响因子:1.651
ISSN:1002-4956
年,卷(期):2024.41(3)
  • 20