Fuzzy controller design without domain experts

The control of nonlinear systems through a self-learning mechanism that can derive the membership functions of the rules used by a fuzzy controller is considered. Without resorting to domain experts, a fuzzy controller has to be constructed that can perform the control task of a regulator problem. The approach is based on the adaptive network, a flexible building block that can be used to implement fuzzy controllers as well as the plants under consideration. The learning rule of adaptive networks can force the plant state to approach a desired state on a time step by time step basis. The proposed approach was used to build a fuzzy controller for balancing an inverted pendulum system. It is shown that only four fuzzy if-then rules are necessary to perform the control task. The controller was quite tolerant to dealing with initial conditions that deviated significantly from the origin. The inverted pendulum system was used to test the proposed control scheme. The simulation results demonstrated its feasibility and robustness