Speed control based on PID optimized by improved whale algorithm
When the turbine speed deviation occurs,the operator needs to manually adjust the PID parame-ters to make the speed stable,but the control effect is not good and the adjustment time is long.To address this problem,an improved whale optimization algorithm is proposed to optimize the PID parameters to con-trol the speed.After introducing reverse learning strategy and nonlinear convergence factors,experiment comparison is carried out in the configuration simulation of a 3MW steam turbine.The results show that compared with whale algorithm and particle swarm optimization algorithm,the improved whale algorithm has better optimization effect and can effectively control the speed of steam turbine.
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