Robust Nonlinear Control of Brushless DC Motors for Direct-drive Robotic Applications
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The control problem associated with brushless DC motors (BLDCMs) for direct-drive robotic applications is considered. In order to guarantee the high-performance operation of BLDCMs in such applications, the effects of reluctance variations and magnetic saturation are accounted for in the model. Such a BLDCM model constitutes a highly coupled and nonlinear dynamic system. Using the transformation theory of nonlinear systems, a feedback control law, which is shown to compensate for the system nonlinearities, is derived. Conditions under which such a control law is possible are presented. The need for the derivation of explicit commutation strategies is eliminated, resulting in reduction of the computations involved. To guarantee the high-performance operation of the system under substantial uncertainties, a robust control law is derived and appended to the overall control structure. The inclusion of the robust controller results in good tracking performance when there are modeling and measurement errors and payload uncertainties. The efficacy of the overall control law is investigated by considering a single-link direct-drive arm actuated by a BLDCM.