Abstract

In permanent magnet synchronous motor (PMSM) speed control, the PI closed-loop control model for current does exist. Although the standard PI closed-loop control has the basic tracking capability from the PMSM control system, however, the expected tracking performance is actually difficult to obtain due to the existence of noise. So in this article, for improvement of the tracking performance, we construct a compensating controller based on extended Kalman filters (EKFs) without changing the existing PI control loop and form a closed-loop controller with enhanced performance. Meanwhile, the gain of the compensating control can be obtained by optimizing the entropy of tracking error. Furthermore, in order to reduce computational resources and improve the accuracy of motor state estimation, we adopt the parallel reduced-order EKFs. All of these are implemented on a single field-programmable gate array (FPGA) chip and verified through simulations. In addition, we also adopt principles of parallel and pipeline design during control framework design based on an FPGA chip, which improve the execution speed of FPGA-based control algorithm and reduced the logic elements used in the chip. Finally, experiments were carried out on a PMSM-based FPGA platform, which verified the feasibility and effectiveness of the proposed PMSM control.

Full Text
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