Intelligent fuzzy logic-based sliding mode control methodologies for pick and drop operation of robotic manipulator

Abstract

The work shows an adaptive control methodology in tracking control of robot manipulators based on amalgamation of fuzzy control with ostensible sliding mode control (SMC). This article proposes different robust adaptive control techniques. Firstly, an adaptive fuzzy PI sliding mode control (AF-PI-SMC) is proposed where fuzzy controller is the major tracking controller and the difference between ideal computational and fuzzy controller is compensated by the compensation controller. Secondly, an auto-tuned adaptive fuzzy sliding mode controller (AT-AFSMC) is proposed where the control gain is considered as individual vector and is adjusted by an adaptive SISO fuzzy system. Mathematical analysis showcases that the controllers in tracking robot manipulator in the presence of uncertainties has global asymptotic stability. Finally, proposed controllers are tested on a 2-degree of freedom (DOF) robot manipulator with real time digital simulator Opal-RT (OP-4500). The experimental results express superiority of the proposed control techniques in presence of uncertainties.