摘要
分数阶PID控制器参数优化是当前分数阶控制领域研究的重要课题,为了避免分数阶PID控制器设计和参数整定的复杂性,提出一种基于改进粒子群算法的分数阶PID参数优化算法。该算法的基本思想是根据正交设计的多因素多水平试验得到改进粒子群算法的参数最优取值,然后使用改进的粒子群优化算法对分数阶PID控制器的参数进行离线优化,从而确定分数阶PID控制器参数的最优取值。通过仿真与遗传算法以及标准粒子群优化算法相比较,仿真结果表明该算法整定参数收敛速度快,且闭环系统的阶跃响应具有超调量小、上升速度快、调节时间短等优点。
Fractional order PID controller parameter optimization is the important subject in the research field of fractional order control, in order to avoid the complexity in the design of fractional order PID controller and tuning of its parameters, a fractional order PID parameter optimization algorithm based on improved particle swarm optimization is proposed. The basic idea of the algorithm is to obtain the optimal parameter value of the improved particle swarm optimization algorithm based on multiple factors and multiple level experiment of orthogonal design, then the improved particle swarm optimization algorithm is used to off-line optimize the parameters of the fractional order PID controller, so as to determine the optimal values of the parameters of the fractional order PID controller. Finally, the algorithm is compared with the genetic algorithm and the standard particle swarm optimization algorithm through simulation, the simulation results show that the proposed algorithm has fast convergence of parameter tuning, and the step response of the closed loop system has advantages such as little overshoot, fast rising velocity, short adjusting time, etc.
作者
郑恩让
姜苏英
ZHENG En-rang JIANG Su-ying(School of Electrical and Information Engineering, Shanxi University of Science and Technology, Xi＇an 710021, China)
出处
《控制工程》
CSCD
北大核心
2017年第10期2082-2087,共6页
Control Engineering of China
基金
陕西省科技厅项目(2012K09-13)
关键词
分数阶PID控制
粒子群优化
遗传算法
参数优化
Fractional order PID control
particle swarm optimization
genetic algorithm
parameter optimization
