基于微粒群算法的模糊滑模控制

针对一类非线性控制系统，提出一种新的基于微粒群算法的模糊滑模控制方法。将模糊控制和滑模控制相结合，利用滑模控制使系统的跟踪误差进入给定的边界层内，启用模糊控制取代切换控制；同时为保证模糊滑模控制系统的全局稳定性，加入监督控制以柔化控制输入；最后基于微粒群算法对滑模面系数和不均匀隶属度函数因子寻优，不仅加快了系统到达滑模面的速度，减小了误差，而且有效地消除了高频抖振。仿真结果表明了该方法的有效性。

Fuzzy Sliding Mode Control Based on Particle Swarm Optimization

Based on particle Swarm optimization, a new design method of fuzzy sliding mode controller is proposed for a class of uncertain nonlinear system. The fuzzy control and sliding mode control is incorporated in this scheme. The tracking error is driven into given boundary layer by the sliding mode control, and then the fuzzy control is a- dopted of the switch control. At the same time, in order to ensure the global stability of fuzzy sliding mode control system, we use supervise controller to smooth the control input. Finally the sliding surface coefficient and the factor of uneven membership function based on soothes method not only speeds up to reach the sliding surface, reduces the steady-state error,but also eliminates the high frequency chattering effectively. The simulation results show the effectiveness of the method.