Abstract
Predictive current control of induction motors can effectively avoid performance deterioration of control caused by delays in the current loop and improve the dynamic performance of current control. However, owing to measurement errors and parameter changes, deviations can appear between the predictive controller parameters and the actual motor parameters. This might lead to static current error, which can cause problems, including decrease in system’s efficiency, inability to deliver nominal torque, and to operate in torque control mode, among others. Based on an induction motor model, this paper quantitatively analyzes the influence on current control stability caused by errors in the predictive control model parameters. In addition, we present the mathematical relation between errors in model parameters and static current error, and propose an algorithm to eliminate this type of error. The algorithm corrected the parameters for predictive control using $dq$ axis current feedback and eliminated the static error caused by parameter mismatch. Through experimental results, the stability and effectiveness of the proposed method were shown.
Published Version
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