Adaptive Control of Robotic Manipulators Using Multiple Models and Switching

This article addresses the tracking control problem of robotic manipulators with unknown or changing dynamics. A novel adaptive control strategy is proposed to improve the overall tracking performance. The proposed method makes use of mul tiple dynamic models of the manipulator in an indirect adaptive controller architecture. The models used for the identification of the manipulator are identical, except for the initial estimates of the unknown inertial parameters of the manipulator and its load. The torque input that is applied to the joint actuators is determined at every instant by the identification model that best approximates the robot dynamics. The mathematical formula tion of the controller algorithm and the stability analysis of the overall system are presented. Simulations and experimental test results are also included to demonstrate the improvement in the tracking performance when the proposed method is used.

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