Abstract
The adaptive inverse control technology is utilized for induction machine (IM) control. Adaptive inverse control is actually an open-loop control scheme and so in the adaptive inverse control the instability problem caused by feedback control is avoided and the better dynamic performances can also be achieved. Linear LMS technique of adaptive inverse control is extended to control the MIMO, nonlinear IM based on BP neural network. And the BP algorithm is improved by using variable learning rate. Simulation study is made to validate the effectiveness of the control scheme.
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