Nonlinear Robust Industrial Robot Control

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Abstract
A new nonlinear robot control scheme is proposed in this paper which is robust against modeling errors and unknown disturbance. The control input consists of a nonlinear part and a linear part. The nonlinear part decouples robot dynamics to obtain a set of equations in terms of each joint’s input and output; the linear part applies robust servomechanism theory to suppress effects of modeling error and unknown disturbance. The nonlinear part can be calculated by using recursive Newton-Euler formulas or parallel processing hardware, and the linear part by dedicated, localized microprocessors. Therefore, this methodology is computationally efficient, and is applicable to general robot configuration. The scheme is applied to control a two-joint, SCARA-type robot. The simulation results demonstrate that this scheme can achieve fast and precise robot motion control under substantial modeling errors.

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