针对常规模糊控制器需要不断手动调整控制器参数才能获得更好控制效果的缺点,提出一种基于多目标遗传算法NSGA-II进行参数优化的路径跟踪模糊控制器。以CJ-1月球探测车原理型样机为研究对象,用模糊逻辑描述了月球探测车的路径跟踪问题,通过调整规则因子来达到调整模糊规则的目的;引入了积分器以达到较好的稳态性能;采用NSGA-II算法实现了控制器7个参数的优化选择,提高控制器的适应能力。仿真结果表明,在跟踪阶跃路径时,常规模糊控制器超调量达到4.25%,而所设计的参数自调整模糊控制器基本能平稳无超调地跟踪路径,获得更好的控制效果。
Facing the fact that traditional fuzzy controller needs to constantly adjust the controller parameters to obtain better control effect,a NSGA-II based parameter optimization path following fuzzy controller is designed for CJ-1 lunar rover.The fuzzy logic technology is used to emulate the characteristics of path following.The optimization for fuzzy rule base is achieved by optimizing fewer rule parameters.An integrator is introduced to achieve good steady-state performance.The NSGA-II algorithm is adopted to achieve auto tradeoff of the parameters.Simulation results show that the designed controller with optimized parameters has better performance than the one with manually regulated parameters.When following a step path,the conventional fuzzy controller overshoot is 4.25%,while the optimized controller can almost follow the path without any overshoot.