The model reference control by adaptive PID-like fuzzy-neural controller

In this paper, an adaptive PID-Like fuzzy-neural controller is proposed and applied to nonlinear model reference control system. For enhancing the flexibility and control capability of the controller we developed, three parameters, including the immediate system error (e(k)), error change (e˙(k)) and the change of error change (ë(k)), are used as the reference inputs for fuzzy-neural tuning mechanism. To demonstrate the superiority of the controller we designed, two types of model reference control systems are studied and simulated. For a comparison, same experiments are also performed by using conventional fuzzy controller with same fuzzy mechanism.