Optimization of Rectification Algorithms for Three-Phase Linear Generation Systems Based on Model Predictive Control

The present study addresses the characteristics of three-phase linear generation systems, such as large amplitudefrequency variations in output electrical energy and periodic changes in phase sequence, by conducting an analysis of the power generation characteristics of linear motors during stable operation and researching the rectification control algorithms for three-phase electrical energy. The parameter design and tuning process for a dual closed-loop controller based on Proportional-Integral (PI) control is complex, computationally intensive, and results in slower system response. Therefore, an improved current inner-loop controller based on Model Predictive Control (MPC) is proposed. This controller can mitigate the impact of uncertainties due to model mismatch, distortion, and disturbances by repeatedly performing online rolling implementations, thereby achieving superior control performance. The paper compares the algorithm proposed in this study with the PI-controlled controllable rectification algorithm in terms of robustness, accuracy, and responsiveness. The results demonstrate that the Model Predictive Controller exhibits better control effectiveness.