Research on Model Predictive Current Control for Induction Machine Based on Immune-Optimized Disturbance Observer

To improve the conventional predictive current control (PCC) performance of an induction machine (IM) system, a robust PCC method based on an immune-optimized disturbance observer (DOB) is proposed in this paper. First, a predictive current controller is established and then the performance of the PCC is analyzed when machine parameters mismatch. Second, the model PCC for an IM based on an immune-optimized DOB is proposed in this paper, and then the performance of disturbance rejection is analyzed. However, the fixed constant time of a traditional DOB will largely limit the performance of a closed-loop system. Therefore, the immune algorithm is introduced in this paper and it is used to optimize the fixed parameters of DOB. Finally, the experimental results show that both smooth dynamic responses at transient-state and high-accuracy performance at steady state can be achieved, and the effectiveness of the proposed algorithm is verified.