摘要
针对复杂的水电站调速系统难以确立精确数学模型导致传统比例-积分-微分(PID)控制器控制精度低、自适应能力差等问题,提出了一种改进磷虾群算法对其PID控制器参数进行优化。对磷虾群算法引入进化因子α以及优化算子β以增加算法自适应调节能力。首先将频率误差以及频率误差变化率代入到改进的磷虾群算法控制器中,通过算法迭代得到一组使目标函数最小的PID参数,将这组参数赋给PID控制器对系统进行控制。仿真结果表明:经过该算法优化后的控制器相较于传统PID控制器超调量明显减小、调解时间大大缩短。
Aiming at the problem that complex turbine governing system is difficult to establish accurate mathematical model,which leads to low control precision and poor adaptive ability of the traditional proportional-integral-differential(PID)controller,an improved krill swarm algorithm is proposed to optimize the parameters of the PID controller.By introducing evolutionary factorsαand optimization operatorsβinto krill swarm algorithm to enhance adaptation and modulability of the algorithm.Firstly,the frequency error and the change rate of frequency error are substituted into the improved krill swarm algorithm controller,and a group of PID parameters which minimize the objective function are obtained by iteration of the algorithm.Then these parameters are assigned to the PID controller to control the system.The simulation results show that compared with the traditional PID controller,the overshoot of the controller optimized by the algorithm is significantly reduced and the mediation time is greatly shortened.
作者
周克良
曾光明
龚达欣
ZHOU Keliang;ZENG Guangming;GONG Daxin(College of Electrical Engineering and Automation,Jiangxi University of Technology,Ganzhou 341000,China)
出处
《传感器与微系统》
CSCD
北大核心
2021年第4期59-62,73,共5页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(61363011)
江西省自然科学基金资助项目(20151BAB207024)。
关键词
频率控制
水轮机调速系统
改进磷虾群算法
进化因子
优化算子
frequency control
turbine speed regulation system
improved krill swarm algorithm
evolutionary factor
optimization operator