Application And Research Of Fuzzy Adaptive Control For The Temperature And Humidity System

Temperature and humidity system is one system which is widely applied in industry, as well as it is one of the most complex control system. In the process of industrial production, it is important to control temperature and humidity parameters, to ensure the quality of the production, but temperature and humidity control is a nonlinear, delay, time-varying complex process, and there is cross coupling between the temperature and humidity. However, the traditional PID control is difficult to achieve satisfactory control effect.Pure lag link to some extent affect the system stability, Smith predictor controller with a forecast model to compensate our prior estimate mathematical model of the object, which time-delay link will be moved to the outside of the closed loop, so as to solve the problem of control object lag, accelerate the response speed of system and reduce regulation time, but as the PID control also needs to know the precise mathematical model. For such system cannot obtain accurate mathematical model, fuzzy adaptive control method provide a better control method. This method not only can adjust system combined with expert knowledge, but also can learn online mathematical model of controlled object. But the deficiency of the fuzzy controller is no integral part, and the lack of a time lag system control.In this paper, we analysis the model of temperature and humidity system. Aiming at the characteristics of temperature and humidity control system, combined with Smith predictive method can effectively overcome the time delay, strong robustness of fuzzy control and PID control high steady state accuracy of the three, we introduce the feedforward decoupling compensator, Smith estimation, adaptive mechanism and fuzzy controller to control the temperature and humidity system, put forward a design method of fuzzy adaptive PID controller- Smith. For system modeling and control provides an effective way, which is of important theoretical and practical significance to study fuzzy modeling and adaptive control.And then, The simulation results show that the adaptive fuzzy PI-Smith controller designed in this paper obtained better effect for the temperature and humidity system in a variety of experimental conditions.