Application of the K-Means Immune Particle Swarm Optimization Algorithm in the Steam Generator Water Level Control

Abstract

The Stability of SG water level plays an important role in the safety of nuclear power plants, but tuned the parameter of water level PID controller is hard. Proposed a novel algorithm, KIPSO, which tuning PID controller parameters. Determine the cluster centre through K-means value cluster algorithm, and take the cluster territory as the characteristic value of vaccine set, enhance the vaccine multiplicity. Updated vaccine extraction by self-adaptive method, improved the convergence and adaptability. Analyzed the algorithm robustness in detail, and gave the rule which the immunity selection parameter. The simulation results shows: compares with the PID controller whose parameters are tuned by ZN method, KIPSO have a smaller overshoot, a better stability, and a shorter adjustment time. The simulation results show that the proposed method is effective for tuning PID parameters.