基于量子遗传算法的模糊滑模控制

针对一类具有不确定性的非线性系统,提出了一种新的基于量子遗传算法的模糊滑模控制器的设计方法.将模糊控制与滑模控制相结合,利用滑模控制使系统跟踪误差进入边界层内;启用模糊控制替代切换控制,并在边界层上通过监督函数平滑控制作用.在滑动模态产生条件下,通过量子遗传算法优化模糊控制器的控制规则,有效地解决了模糊滑模控制中模糊控制规则的确定问题,从而削弱了系统的抖振,改善了控制器的控制性能.仿真结果表明了该方法的有效性.

Fuzzy Sliding Mode Control Based on Quantum Genetic Algorithm

Based on quantum genetic algorithm,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 drove into boundary layer by the sliding mode control,and then the fuzzy control is adopted instead of the switch control.At the same time,the control effort is smoothed by the supervision function on the boundary layer.The quantum genetic algorithm is used to optimize the fuzzy rules of the fuzzy controller under the condition of sliding mode caused,and the fuzzy rules are defined efficiently,so that the chattering of the system is weakened and the performance of the controller is improved.The simulation result shows the effectiveness of the method.