Adaptive chattering-free sliding mode control design using fuzzy model of the system and estimated uncertainties and its application to robot manipulators

This paper presents design and implementation of a novel adaptive chattering-free sliding mode control (ACFSMC) scheme and its application to motion control of robot manipulators. Due to the presence of complex phenomena such as large flexibility, model uncertainties, and external disturbances a robust and adaptive control is required to control the motion of the robots. This paper presents the design of an adaptive chattering-free sliding mode control using two adaptation mechanism namely: a fast and performance-based online estimation of uncertainties, which is constructed based on the dynamic behaviour of a sliding function; and an adaptive fuzzy model of the robot, which is constructed using a systematic fuzzy modelling method and from input-output data of the robot through system identification. These two adaptation mechanism can be interpreted as the integration of fast response to immediate feedback information and the response based on the knowledge that has already been built into the fuzzy model of the controller, which is the model-based component of the ACFSMC. The global stability and robustness of the proposed controller are established using Lyapunov's approach and fundamentals of sliding mode theory. Based on the simulations and experimental results, the proposed controller performs remarkably well in comparison to SMC with boundary layer and the high gain proportional-integral-derivative (PID) controllers in terms of the tracking error convergence and robustness against uncertainties.