Performance optimization for steam generator level control based on a revised simultaneous perturbation stochastic approximation algorithm
With the development of intelligent technology, the nuclear power plant(NPP) is getting more and more smarter. For the traditional nuclear power plant, the performance of the steam generator level control was greatly determined by a group of preset control parameters. Usually, these parameter settings were not optimal because the tuning process was experience-based, cumbersome and time-consuming. To improve the control performance and make the NPP more smarter, in this paper, a revised Simultaneous Perturbation Stochastic Approximation algorithm(SPSA) was proposed to optimize the control parameters of the steam generator level control system. The effectiveness of this method has been demonstrated through simulation experiments.