Controlled nonlinear systems using fuzzy input adaptive networks

This paper presents a parallel adaptive networks controller which is implemented by our Fuzzy Input Adaptive Network (FIAN). The FIAN is easy to be set initial parameters and structure by the human sense. All FIAN parameters can be adjusted by gradient descent based on Lyapunov stability synthesis during the operation of networks. The gradient adaptive is applied via linear plant parameters approximation at the chain rule of gradient search, The performance of FIAN as controller can be shown by its application which is the controllers for nonlinear plants. Due to our experiments "water bath temperature control system" and "single inverted pendulum" are selected to test the system performance.