基于IGWO-PID预测算法的水轮机调速控制

Hydraulic turbine speed control based on IGWO-PID prediction algorithm

针对水轮机调速系统存在非线性、时变性、滞后性导致传统PID控制器超调量大,调节精度低等缺点,引入改进灰狼(IGWO)算法对传统PID控制器进行优化,在原灰狼算法的基础上通过改进线性收敛因子提高种群的收敛速度,结合变异算法对较优灰狼个体进行变异操作,通过模拟退火算法对变异后的新个体进行概率性选择,使用动态矩阵对预测频率进行实时在线校正,更新优化出一组最合适的PID参数,通过对系统加入负荷扰动对水轮机调速系统的动态特性,结果表明,改进的灰狼算法PID控制器性能要远优于传统PID控制器,调节精度更准、调节时间大大缩短。

In view of the non-linearity,time-varying nature and hysteresis of the hydraulic turbine speed control system,the traditional PID controller has large overshoot and low adjustment accuracy,so an improved gray wolf optimization(IGWO)algorithm is introduced to optimize the traditional PID controller.On the basis of the original GWO algorithm,the linear convergence factor is improved to increase the convergence speed of the population.The mutation operation is carried out on the superior grey wolf individuals in combination with the mutation algorithm.The simulated annealing algorithm is used to probabilistically select the new individuals after mutation.The dynamic matrix is used to conduct real-time online correction of predicted frequency,so as to update and optimize a set of most suitable PID parameters.The dynamic characteristics of the hydraulic turbine speed control system is improved by adding load disturbance to the system.The results show that the performance of the PID controller optimized by the IGWO algorithm is much better than that of the traditional PID controller.Its adjustment accuracy is higher and its adjustment time is greatly shortened.