Work

Research on Improved Incremental Deadbeat Predictive Current Control Method for Low-Speed Permanent Magnet Machine

Year: 2026

Type: article

Abstract: Permanent magnet synchronous motors (PMSMs) operating at low speeds are susceptible to parameter mismatches, periodic harmonics, and various internal and external disturbances, which result in steady-state current errors and low-frequency speed oscillations. To address these issues and improve low-speed PMSM performance, an automatic tuning disturbance rejection incremental deadbeat predictive current control (AT-DR-IDPCC) method is proposed. First, an incremental extended-state observer (IESO) is incorporated into the incremental deadbeat predictive current control (IDPCC) framework to estimate and compensate for lumped disturbances caused by resistance and inductance mismatches, thereby improving parameter robustness. Meanwhile, a quasi-resonant controller (QRC) is connected in parallel with the current loop to selectively suppress sixth-order current harmonics induced by inverter nonlinearities and flux harmonics. Furthermore, a deep deterministic policy gradient (DDPG)-based parameter optimization scheme is introduced to automatically tune the controller parameters, overcoming the limitations of conventional trial-and-error tuning and achieving the coordinated optimization of dynamic response, steady-state accuracy, and disturbance rejection capability. Simulation and experimental results demonstrate that, compared with proportional–integral (PI) control and IDPCC incorporating the IESO (IESO-IDPCC), AT-DR-IDPCC reduces the phase current’s total harmonic distortion (THD) by 56.1% and 23.7% while also decreasing the speed fluctuation amplitude by approximately 50% and 20%, respectively. The proposed method significantly enhances the robustness, harmonic suppression capability, and low-speed control performance of PMSM drives.

Source: Electronics

DOI: 10.3390/electronics15173790

Authors: Junlong Zhang, Shaoqin Xie, Hong Chen, Guanhong Gao, Fuhao Wang

Institution: Shandong University of Science and Technology

Language: English

Topic: Sensorless Control of Electric Motors

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,896