Least Squares Adaptive Control for Trajectory Following Robots

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Abstract
A control scheme is presented for trajectory following with robotic manipulators. The method employs a feedforward torque for gross compensation and adaptive feedback gain scheduling for correcting deviations from the desired trajectory. The adaptive controller eliminates trajectory errors in the least squares sense without using online identification or a reference model. The control scheme takes into account dynamic nonlinearities (e.g., coriolis and centrifugal accelerations and payload changes), geometric nonlinearities (e.g., nonlinear coordinate expressions for large excursions) and physical nonlinearities (e.g., nonlinear damping) as well as dynamic coupling present in a manipulator. The method can accommodate real-time changes in the desired trajectory. In practice, a recursive algorithm would be needed to accomplish this. Computer simulations are given to demonstrate the feasibility of the control scheme.

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