Artificial Immune System And Its Application Research For Power Plant Control

Artificial immune controllers are designed based on immune feedback. And Adaptive Immune Genetic Algorithm (AIGA) are given via immune principle, and applied in power plant control systems by simulation.First:Fuzzy immune self-tuning PID control is addressed by considering immune feedback control, fuzzy control and PID control. And it is proved to have good rapidity and anti-disturbance by using simulation in mill load control system.Second:Based on the full analysis of incomplete differential and the inner loop role of cascade control, immune incomplete differential PID-immune P cascade control is designed and applied to feed water system in power plant. Simulation results show that, the feed water system adopting the control strategy has good rapidity, and has ability to overcome the feed-water disturbance and the steam disturbance. And the false level greatly reduces.Third:Fuzzy immune-Smith control is addressed in this paper. Smith control can be used to solve large delay. Fuzzy immune control can solve the rapidity, anti-disturbance, and system stability when model does not match. Applied to feed water system, simulation results show that the improved fuzzy immune-Smith control has better rapidity and anti-disturbance than Smith control.Fourth:Immune internal model controller is designed. Combining immune control and Internal Model Control, filter parameters can be tuned online, and the contradiction between Internal Model Control and robustness is solved. This controller is applied to simulate for mill load control system. Simulation results show that immune internal model has better rapidity and anti-disturbance than Internal Model Control.Fifth:Based on density regulation of biological immune theory, diversity preservation strategy and immune memory function, Adaptive Immune Genetic Algorithm is proposed. Simulation results show that Adaptive Immune Genetic Algorithm is better than genetic algorithm on searching ability.Sixth:The Adaptive Immune Genetic Algorithm is used for PID parameters optimization for main steam temperature control system in power plant, and load dispatching optimization of power plant unit. Simulation results show that Adaptive Immune Genetic Algorithm improves the convergence rate, and maintains the antibodies diversity. Adaptive Immune Genetic Algorithm is stronger than Genetic Algorithm on optimization capability and convergence speed. That is helpful for on-line optimization in power plant.