Fuzzy Rules Emulated Discrete-Time Controller Based on Plant's Input-Output Association

In this work, an adaptive controller is designed by an adaptive network called fuzzy rules emulated network (FREN) for a class of nonlinear discrete-time systems when the mathematical model is completely neglected. The characteristic curve between the plant's input and output is drawn by results of the experimental setup. The design parameters are determined by the characteristic curve and utilized to design the controller. The network structure of FREN controller is established by the set of human knowledge-based IF-THEN rules according to the relation between the plant's input and output. The theoretical result is provided to guarantee the convergence of tracking error of the learning algorithm. Furthermore, experimental systems with the LED current control and the robotic system are constructed to validate the performance of the proposed controller.