PSO算法用于导弹鲁棒控制器性能权函数优化

摘要

在导弹μ综合鲁棒控制器的设计中,性能权函数的设计通常只能采用尝试和仿真迭代方法.这种设计方法繁琐费时,控制性能不确定.该文采用粒子群优化(particle swarm optimization,PSO)算法自动设计性能权函数.分析了性能权函数各项系数对闭环响应的影响,设计了PSO优化算法的各项参数,并对PSO算法和μ控制进行综合设计.仿真结果表明,采用优化后性能权函数获得的μ控制器性能良好,性能指标函数具有较好的收敛特性,表明了该方法的有效性.%In the missile u, robust controller design, the design of performance weighted function is difficult and time-consuming. Traditionally, one can only use trial-and-error or simulation methods, and therefore the controller's overall performance cannot be guaranteed. In this paper, a particle swarm optimization (PSO) algorithm is used to optimize the performance weighted function automatically. By analyzing each parameter of the weighted function, parameters of the algorithm are selected. So the PSO algorithm and the u controller design process can be combined. Simulations show that the u controller can meet the requirements of control performances using the optimized performance weighted function. The objective function is convergent, and effectiveness of the method is confirmed.