Work

Disturbance Pre-Estimation Based Receding Horizon Predictive Control for PMSM Drives

Year: 2025

Type: article

Abstract: In this article, a disturbance pre-estimation based receding horizon prediction control (DPE-RHPC) method is proposed to address the limitations of traditional methods in terms of poor system dynamic performance and robustness caused by dynamic disturbances. The DPE-RHPC introduces a generalized receding horizon estimator (GRHE) to estimate the lumped disturbances and high-order derivatives in the velocity and current loops, thereby constructing a disturbance dynamic sequence that can predict the future behavior of disturbances. Combined with the multi-step predictive control method, it provides additional disturbance dynamic information for long horizon optimization problems without increasing computational burden. By utilizing the disturbance dynamic information and combining it with receding horizon optimization of predictive control, the prediction model is updated to improve prediction accuracy and demonstrate better control performance. The effectiveness of the proposed method is verified through simulation and experimental results.

Source: IEEE Transactions on Power Electronics

DOI: 10.1109/tpel.2025.3577447

Authors: Junxiao Wang, Zihao Chen, Ruocheng Wang, Yimeng Li, Jun Yang, Jose Rodriguez

Institutions: Zhejiang University of Technology, Southeast University, Loughborough University, Universidad Andrés Bello

Language: English

Topic: Advanced Control Systems Optimization

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funder: National Natural Science Foundation of China