矢量推力机电作动控制系统优化方法研究
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摘要
随着导弹、火箭等特殊飞行器的机动性需求日益提高,矢量推力控制技术变得十分重要。但矢量推力机电作动系统是高阶、大惯量对象,因此其控制器参数的整定较为困难,且整定效果往往不够理想。针对上述问题,考虑到粒子群优化(PSO)算法全局寻优能力强、算法简单、易于实现等特点,采用PSO算法来优化控制器参数(控制增益)。对典型的飞行器矢量推力机电作动系统进行了研究,并建立了其数学模型。将控制增益整定等效为优化问题,采用PSO算法优化控制器参数。对优化后的矢量推力机电作动控制系统进行仿真,结果表明,该闭环系统单位阶跃响应的调节时间小于1 s、超调量为0.505%,同时喷管转动可以快速且准确地跟踪位置指令信号。仿真结果表明,优化后的控制器对该作动系统的控制效果良好,也验证了应用PSO算法解决控制优化问题的可行性。
With the increasing demand for maneuverability of special aircrafts,such as missiles and rockets,thrust vector control technology has become more and more important. However,the thrust vector electromechanical actuation system is a high order object with large inertia,so the tuning of the parameters of its controller is very difficult,and the control effect is often not ideal. In view of the problems above,considering the particle swarm optimization( PSO) algorithm features strong capability of global optimization,simple and easier to implement,thus the PSO algorithm is adopted to optimize parameters of controller( control gain).Firstly,the typical thrustvectorsystem with electromechanical actuator is researched,and its mathematical model is setup. Then,the control gain tuning is equivalent to optimization problem,the control parameters are optimized by using PSO algorithm. Simulation of the optimized thrust vector controlsystem is carried out,and the results show that settling time of unit step response is less than 1 s,with 0. 505% overshoot,while nozzle position tracks the command signal quickly and accurately. This indicates the good control effect of optimized controller and verifies the feasibility of applying PSO to solve the problem of controller optimization.
With the increasing demand for maneuverability of special aircrafts,such as missiles and rockets,thrust vector control technology has become more and more important. However,the thrust vector electromechanical actuation system is a high order object with large inertia,so the tuning of the parameters of its controller is very difficult,and the control effect is often not ideal. In view of the problems above,considering the particle swarm optimization( PSO) algorithm features strong capability of global optimization,simple and easier to implement,thus the PSO algorithm is adopted to optimize parameters of controller( control gain).Firstly,the typical thrustvectorsystem with electromechanical actuator is researched,and its mathematical model is setup. Then,the control gain tuning is equivalent to optimization problem,the control parameters are optimized by using PSO algorithm. Simulation of the optimized thrust vector controlsystem is carried out,and the results show that settling time of unit step response is less than 1 s,with 0. 505% overshoot,while nozzle position tracks the command signal quickly and accurately. This indicates the good control effect of optimized controller and verifies the feasibility of applying PSO to solve the problem of controller optimization.
引文
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[2]伍城.推力矢量控制装置与测试系统研究与设计[D].上海:上海应用技术学院,2015.
[3]SCHINSTOCK D E,HASKEW T A.Identification of continuous-time,linear,and nonlinear models of an electromechanical actuator[J].Journal of Propulsion&Power,1997,13(5):683-690.
[4]LI Y,LU H,TIAN S,et al.Posture control of electromechanicalactuator-based thrust vector system for aircraftengine[J].IEEE Transactions on Industrial Electronics,2012,59(9):3561-3571.
[5]刘晓峰,陈通.PSO算法的收敛性及参数选择研究[J].计算机工程与应用,2007,43(9):14-17.
[6]杨诚,杨传启.基于粒子群算法的PID参数优化[J].自动化仪表,2006,27(s1):95-96.
[7]GAO Y,GU L,PAN L.Application of variable structure control in missile electromechanical actuator system[C]//International Conference on Intelligent Computation Technology and Automation.IEEE,2008:313-316.
[8]EBERHART R,KENNEDY J.A new optimizer using particle swarm theory[C]//International Symposium on MICRO Machine and Human Science.IEEE,2002:39-43.
[9]KENNEDY J,EBERHART R.Particle swarm optimization[C]//IEEE International Conference on Neural Networks,Proceedings.IEEE,2002:1942-1948.