Research On The Method Of Synchronous Generator Excitation System Intelligent Control

Based on synchronous generator excitation control system of complex nonlinearand comprehensive analysis of characteristics of synchronous generator, then, combinedwith fuzzy theory to advance intelligent optimization method, this research furthercarries out the study of the theory of the nonlinear excitation control system, andproposes the particle swarm optimization algorithm of fuzzy adaptive intelligentoptimization method of excitation control strategy system.First of all, aiming at the huge synchronous generator excitation systemrequirements, this research establishes mathematical model of each link, analyzes thebasic control law of excitation system and its static and dynamic characteristics. Bysimplifying theoretical models accordingly with practical excitation control system tomeet engineering requirements, provides theoretical support for the research of a laterchapter.It is a hotspot in intelligent optimization methods in recent years. Due to thissituation, this research deeply analyzes of particle swarm optimization mechanism andcome up with adaptive particle swarm optimization. By listing instance simulation,compares the algorithm with the other common particle swarm algorithm in thecalculation of excitation system control precision and convergence speed.Specific to the synchronous generator excitation control system of complexnonlinear and combine with fuzzy theory and classical PID control law, this researchputs forward a nonlinear system parameters optimization strategy. Based on the existingfuzzy model, design a fuzzy PID excitation controller based on Mamdani fuzzy model,and unconsidered system precise modeling condition to realize the stability control ofexcitation system in many conditions and through contrast experiment to verify theeffectiveness of the proposed method.Finally, this research bonds the nonlinear system control advantages on fuzzycontrol and particle swarm optimization algorithm for parameters optimization ofadvantage to form intelligent control of fuzzy adaptive PID excitation control strategy.The general blue print is selected the initial parameters of the system by using PSOalgorithm at first, and then controlled by the FAPID for dynamic system. This strategyis controlled easily and highly accurate, which is linked to excitation control rules withflexible and changeable reaction system, making the system to reach steady state timely.