基于混沌粒子群算法的PI控制器参数在线整定

摘要

针对PI参数人工调节费时、费力且往往结果不甚理想的问题,并针对粒子群算法易局部收敛的缺陷,采用引入混沌搜索思想的混沌粒子群算法,提出一种在线PI控制器参数整定方法.以PMSM控制系统为对象,对该方法进行了测试,测试结果显示,采用参数整定后的PI控制器,PMSM控制系统拥有良好的动态和稳态性能,证明了基于混沌粒子群算法的PI参数整定方法的可行性.%For the problem that manual parameter adjustment of PI controller costed too much time and energy,but few results were satisfactory,a method based on chaotic particle swarm optimization (CPSO) algorithm was proposed for online parameter adjustment of PI controller. The chaotic search theory was brought in because of the premature convergence of particle swarm optimization (PSO) algorithm. Then the method was tested with PMSM control system. The results of tests indicate that the PMSM has excellent dynamic and static performances with the optimized PI controller. The method based on CPSO algorithm is effective and feasible for online parameter adjustment of PI controller.