Robust control strategy for electrically driven robot manipulators: adaptive fuzzy sliding mode

Abstract

In this study, a sliding mode controller is designed to control the position tracking of robot manipulator. The proposed control has global asymptotical stability in the presence of structured uncertainties, un-structured uncertainties and un-modelled dynamics of the robot manipulator as well as in motors dynamics. The proposed control structure is designed in such a way that initially, by using inverse dynamic method, it reduces the uncertainties bound and finally, sliding mode control eliminates the influence of the remaining uncertainties in closed-loop system stability. Further, in control input for eliminating undesirable chattering phenomena using the fuzzy logic, an adaptive fuzzy approximator is designed in such way that approximates the uncertainty bounds. Mathematical proof shows that the adaptive fuzzy sliding mode control of a closed-loop system has global asymptotical stability. Since the number of existing fuzzy rules are low in adaptive fuzzy approximator rules base and in single input–single output form, so control input computational load is very low and this order makes the proposed control of practical implementation possible. To evaluate the performance of the proposed controller, a case study on a robot manipulator with two degrees of freedom is implemented. Simulation results show the desired performance of the proposed controller.