基于粒子群优化的一类模糊控制器设计

针对一般模糊控制器存在稳态性能与动态性能之间的矛盾,提出一种参数自整定模糊控制器.该控制器结构简单,算法简便,具有良好的动态特性,能有效消除静态偏差,且有一定的鲁棒性.为避免模糊控制器设计中参数调试的复杂性,获得最佳的控制性能,应用改进的自适应粒子群优化算法对模糊控制器参数进行优化设计.通过典型的被控对象的仿真研究,验证了所提出算法的有效性和适应性以及所设计控制器的优越性.

Design of fuzzy controller based on particle swarm optimization

A fuzzy controller with parameter self-tuning structure is proposed for solving the contradiction between the steady performance and dynamic performance of usual fuzzy controllers.The obtained controller has good dynamic performance and robustness,the structure of which is simple and the algorithm is convenient,which can effectively eliminate steady state deviations.For avoiding complex adjustment of parameters in the design of fuzzy controllers and attaining optimal control properties,a modified self-adaptive particle swarm optimization(PSO) algorithm is applied to optimizing the parameters of a fuzzy controller during design.Numerical simulations based on typical controlled objects show the effectiveness and the adaptability of the algorithm,as well as the superiority of the designed controller.