Optimal Control of Nuclear Power Plant Steam Generator Based on GMFAC

According to the nonlinear control system of steam generator water level, large lag and the "false water level" caused by load changes and other issues, based on the model free adaptive control（MFAC） theory, an improved model free adaptive control（GMFAC） theory which is based on high"universal model" is proposed, and the relevant controller is designed to control the water level of steam generator.For the model free adaptive control parameter optimization problem,A swarm intelligence optimization algorithm based on animal behavior — artificial fish swarm algorithm（AFSA） is proposed.In order to avoid the local optimum and improve the convergence rate, an improved AFSA algorithm（PSO-AFSA） is proposed.In order to improve the accuracy of the algorithm and to improve the accuracy of the algorithm, a reference particle swarm optimization（PSO） algorithm is defined to improve the accuracy of the algorithm.The simulation results show that the GMFAC has better performance and disturbance rejection ability after optimization of the artificial fish swarm algorithm.