Research On Generator Fuzzy Neural PID Based On PSO Excitation Control Strategy

The generator excitation control system is the important part of the power system.It can effectively guarantee the voltage quality and enhance the run stability of thepower system. Therefore, excitation control has the decisive significance to the runningof the entire electrical power system. At present, scholars at home and abroad combinethe PID control with fuzzy control belong to intelligence control theory, exploit to thefully their favorable conditions and avoid unfavorable ones, and develop fuzzy PIDexcitation controllers. However, the general fuzzy controller can't adapt the systemparameters because the controller factors can't be changed once seted. Therefore, thefuzzyPID controller needs further improved.The development and actuality of generator excitation control rules are analyzedin this thesis. Based on the fuzzy control theory and the neural network control theoryand PSO algorithm theory, one kind by the fuzzy neural network and the PID neuralnetwork series union control policy is put forwarded with time change quality andnonlinearity of controlled plant considered, and has designed the fuzzy nerve PIDexcitation controller. The controller fused merits of the fuzzy control, the neuralnetwork control and conventional PID controls, which not only maintain simplity andthe precision high characteristic of PID control but also display the fuzzy control to benimble fully and the rapid good merit. Then this fuzzynerve PID excitation controller'srelated parameter are optimized by improved PSO algorithm, and thus the excitationcontroller's true intellectualization has been realized. At last, the simulation research iscarried out, and the results indicate that the excitation controller designed in this thesishas better controlling effect than the general PID excitation controllers do.