Fuzzy-neural-Based PID Control And Simulation Of Hydro-turbine Governing System

Hydro-turbine governing system is an important part of hydropower system, the quality of governing System deeply affact production efficiency and safety.Normal PID controller has been applied in most governing system. Although it is simply and with better robustness, it can not realize parameter self-adjustment. This paper proposes a fuzzy-neural–based PID controller, neural network helps fuzzy controller to study, while fuzzy controller helps neural network to initialize. This method remains advantages of PID controller, furthermore makes the goal funtion of pratical output and network output smaller so as to modify parameter of PID controller. The simulation result proves that the transient process performance of the former is better with shorter adjust time and smaller over value than normal PID controller.This paper introduces the proposal and significance of the project, sums up the aim and development and model of hydro-turbine governing system. Then, summarizes the theory of fuzzy control, neural network, their advantages and disadvantages, their development and applications.Then proposes a fuzzy-neural–based PID controller with combination of fuzzy and neural. This algorithm can adjust PID parameter on line with a RBF identification.Then, makes a simulation with the fuzzy-neural–based PID controller for a simple hydroturbine model. The result proved that the transient process performance of the former is better with shorter adjust time and smaller over value.In the end, sums up the work of this paper, points out the shortage of this paper, and the further work to be developed.