Sliding Mode Control Based on Synthesis of Approximating State Feedback for Robotic Manipulator

Abstract

In this paper, three paradigms are used to deal with a robot manipulator control problem. These paradigms are feedback linearization method, approximating control by Taylor truncation, and sliding mode approach. Robotic manipulator is highly nonlinear, highly time-varying, and highly coupled. In robotic manipulator there are many uncertainties such as dynamic parameters (eg., inertia and payload conditions), dynamical effects (e.g., complex nonlinear frictions), and unmodeled dynamics. The classical linear controllers have many difficulties in treating these behaviors. To overcome this problem, sliding mode control (SMC) has been widely used as one of the precise and robust algorithms. Application of traditional SMC in nonlinear system uses exact feedback linearization. Geometric differential theory is used to develop exact linearization transformation of nonlinear dynamical system, by using nonlinear cancellation and state variable transformation. Hence, the controller can be synthesized by using the standard sliding mode for linear system. The main weak point of the exact linearization is that its implementation is difficult. This study presents a synthesis SMC based on approximating state feedback for robotic manipulator control system. This approximating state feedback is derived from exact feedback linearization. Based on approximating state feedback, sliding mode controller is derived. The closed loop stability is evaluated by using the Lyapunov like theory.