Design of an enhanced adaptive self-organizing fuzzy sliding-mode controller for robotic systems

Abstract

It is difficult to determine the stability of a self-organizing fuzzy controller (SOFC). Therefore, a system controlled using the SOFC cannot guarantee the stability of the system during the control process. To eliminate the problem caused by the SOFC, this study developed an enhanced self-organizing fuzzy sliding-mode controller (EASFSC) for robotic systems. Instead of using the system’s output error and its error change, the EASFSC uses a sliding surface and its differentiation as the input variables of a fuzzy logic controller (FLC) in the SOFC. Using the fuzzy operation, these variables generate a control input that ensures the stability of the system. The proposed method also employs an adaptive law to modify the fuzzy consequent parameter of the FLC in the SOFC to improve the control performance of the system. The stability of the EASFSC has been proven using the Lyapunov stability theorem. Simulation results of a two-link robotic manipulator application verified that the EASFSC provides superior control performance as compared with the SOFC.