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Sequential Direct Speed Predictive Control Of Pmsm With Two-Step Compensation Cover

Sequential Direct Speed Predictive Control Of Pmsm With Two-Step Compensation

Open Access
|Jun 2026

Abstract

Recent progress in model predictive control of permanent magnet synchronous machines (PMSMs) shows that sequential direct speed predictive control (S-DSPC) offers a promising alternative of eliminating weighting factors in the cost function. This paper presents a simulation-based validation of an S-DSPC strategy with computational delay compensation, where cost functions are evaluated sequentially to simplify weight tuning and reduce complexity. A linear Kalman filter–based load torque observer provides the torque estimation required for state prediction. To study the effects of delay, a computational delay is introduced, and a compensation algorithm is proposed. The method addresses real-time predictive control delays by advancing state predictions to the k + 2 sampling step, ensuring that the applied switching state reflects actual system conditions. The approach was tested in MATLAB/Simulink under three cases: delay without compensation, delay with compensation, and an ideal delay-free case. Results show that uncompensated delay causes distortion in dq-axis currents and increases the total harmonic distortion (THD) of phase currents. With the two-step compensation (TSC) method, THD was reduced by approximately 35% compared to the uncompensated case, achieving performance close to the ideal scenario. Speed tracking and transient responses remained largely unaffected, confirming that TSC effectively improves current quality in S-DSPC.

DOI: https://doi.org/10.2478/aei-2026-0012 | Journal eISSN: 1338-3957 | Journal ISSN: 1335-8243
Language: English
Page range: 64 - 70
Submitted on: Aug 28, 2025
Accepted on: Nov 21, 2025
Published on: Jun 17, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2026 Lukáš Pancurák, Karol Kyslan, published by Technical University of Košice
This work is licensed under the Creative Commons Attribution 4.0 License.