Intelligent Control Of Hydraulic Servo Position System

This paper is a theoretical research that is based on the having been finished project of the state ''the ninth five years" tackling key scientific and technological problems and facing the continuous casting analogy device in the laboratory of our school. It is difficult for the hydraulic servo position system to solve the problem that is caused by the parameters variety, outside disturbance and the friction nonlinear dead zone of the valve. It is well known that it is not necessary to get an accurate model of the system for fuzzy control. We also know that neural network can solve the problems caused by non-linear effectively. So the research that two methods are applied to control the hydraulic servo position system has practical meaning and theory value.According to analysis the frequency graph tested by 1250 frequency detector, the high order mathematical model can be deduced. Then we get a simplified mechanism model by combining the practical model and use the simplified model to design the controllers. On the basis of the summary of the characteristics and application of fuzzy control and neural network theory, a self-tuning fuzzy control, a model reference fuzzy adaptive controller, a fuzzy neural network based on fuzzy hierarchy error approach and a neural network variable structure controller are proposed. In the fourth controller, a neural network is used to identify the friction nonlinear dead zone of the valve, and then another neural network is used to fit the inverse model of the nonlinear for compensating the nonlinear and a variable structure controller is designed to control the hydraulic servo position system. And the problem of the friction nonlinear dead zone of the valve is solved. The result of simulation shows that hydraulic servo position control system has good performances in the dynamic and static state control accuracy, which shows the feasibility of these control methods.