摘要
分数阶PI^λD^μ控制器具有5个控制参数,相比于传统PID控制器具有更高的控制精度及灵活度。将分数阶PI^λD^μ控制器应用于BLDCM调速系统可有效提高其性能指标。但由于增加了控制参数λ和μ,参数整定难度也相应提高。提出一种通过改进的粒子群算法对分数阶PI^λD^μ控制器参数寻优的方法,并引入自适应权重策略和混沌局部搜索策略来克服普通粒子群算法容易陷入局部最小解及收敛速度慢的不足。仿真和系统实际运行效果都证明该方法的可行性。
Fractional order PI^λD^μ controller with 5 control parameters,compared with the traditional PID controller,has higher control precision and flexibility. The fractional PI^λD^μ controller used in BLDCM control system can improve the performance effectively. However,due to the increase of control parameters,the difficulty of parameter tuning was also improved higher. A method of optimizing the fractional order PI^λD^μ controller parameters based on the improved particle swarm optimization algorithm was proposed,and the strategies of adaptive weight and chaotic local search can overcome the problem that the particle swarm algorithm is easy to fall into the minimum local solution and its slow convergence. The feasibility of this method was proved by the simulation and the system＇s practical operation.
出处
《微特电机》
北大核心
2016年第7期59-62,71,共5页
Small & Special Electrical Machines
基金
辽宁省教育厅科学研究一般项目(L2012497)
关键词
BLDCM
分数阶PI^λD^μ
参数整定
粒子群算法
brushless DC motor（BLDCM）
fractional order PI^λD^μ
parameter tuning
particle swarm optimization
