Abstract

In this paper, a controller is proposed that is able to overcome existing structured and unstructured uncertainties in the dynamic equations of robot manipulator and its actuators. In this method, at first, through sliding mode control and by using defined dynamic equations of robot manipulator, robust nonlinear controller is designed that is capable of overcoming the existing uncertainties. In the following, due to incidence of the control input chattering, a first-order TSK fuzzy approximator is designed in such a way that is able to overcome undesirable chattering phenomenon. The presented fuzzy sliding mode control has a small number of calculations. However, the design structure of proposed control is in such a way that leads to increase the number of needed sensors for the practical implementation of this controller. Next, to overcome these problems, an adaptive fuzzy approximator is used to approximate the bounds of the existing uncertainties. The proposed adaptive fuzzy sliding mode control has low volume of calculations, and due to the use of single-input, single-output fuzzy rules in the adaptive fuzzy approximator, the problem of the increasing number of sensors is resolved. Mathematical proof investigates that a closed-loop system with the proposed control and in the presence of existing uncertainties in the dynamic equations of robot manipulator and its actuators has global asymptotic stability. Finally, to demonstrate the performance of the proposed controller, a two-link elbow robot manipulator is used as a case study. The simulation results show the favorable efficiency of the proposed controller.

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