Grey Wolf Optimization Algorithm Based State Feedback Control for a Bearingless Permanent Magnet Synchronous Machine

In this article, an optimal control strategy for a bearingless permanent magnet synchronous machine (BPMSM) drive is proposed. The state feedback control (SFC) based on the grey wolf optimization (GWO) algorithm is applied. As for the BPMSM system, coupling and nonlinearity exist, which hinders the SFC. Hence, the linearization of the BPMSM mathematical model is implemented first. Second, the discretized state model with the augmented integrals of the displacement error and the angular speed error is obtained. Then, the weighting matrices
$K_{d}$
are obtained by employing the GWO algorithm. Finally, simulations and experiments are carried out to verify the effectiveness of the proposed method. Comparisons between the controllers with and without the penalty term are conducted. Meanwhile, the proportional-integral (PI) controllers based on the genetic algorithm and the proposed one are compared as well. The results show the superiority of the proposed method reflecting in faster response and no overshoot compared with the PI controllers.