Model-free sliding mode control for PMSM based on adaptive super-twisting reaching law

Permanent Magnet Synchronous Motors (PMSMs) are core actuators in electric drive systems for their high-power density and precision, but their control performance and robustness degrade severely under disturbances, abrupt load changes and parameter perturbations. Conventional Sliding Mode Control (SMC) has strong robustness but suffers from inherent high-frequency chattering and poor fixed-gain adaptability, failing to meet stringent high-precision electric demands. To address these issues, this paper proposes a novel model-free sliding mode control strategy (MFITISMC–ADSTA–TISMO) integrating improved terminal integral sliding mode, adaptive super-twisting reaching law and improved Terminal Sliding Mode Observer (TISMO) for high-precision PMSM control. The core contributions are: 1). A novel PMSM ultra-local model incorporating state gains and lumped unknown disturbances is constructed, eliminating accurate motor model dependence and fundamentally eradicating model mismatch errors. 2). An improved terminal integral sliding mode surface with continuous smooth nonlinear functions is designed, which, combined with the adaptive super-twisting reaching law, ensures finite-time state convergence and mechanism-level chattering suppression. 3). An improved terminal sliding mode observer is developed to accurately estimate and compensate for total system disturbances in real time, significantly enhancing disturbance rejection under complex conditions. Experimental results demonstrate that the proposed strategy outperforms traditional methods in dynamic response, steady-state accuracy, multi-condition disturbance rejection and parameter robustness, validating its engineering value in high-performance electric drive control.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-04-25
DOI
https://doi.org/10.1038/s41598-026-50065-5
Primary Topic
Sensorless Control of Electric Motors
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Model-free sliding mode control for PMSM based on adaptive super-twisting reaching law

Weiwei Li, Wenhua Yao
Scientific Reports
Sensorless Control of Electric Motors
article

Model-free sliding mode control for PMSM based on adaptive super-twisting reaching law

Weiwei Li, Wenhua Yao
article en

Abstract

Permanent Magnet Synchronous Motors (PMSMs) are core actuators in electric drive systems for their high-power density and precision, but their control performance and robustness degrade severely under disturbances, abrupt load changes and parameter perturbations. Conventional Sliding Mode Control (SMC) has strong robustness but suffers from inherent high-frequency chattering and poor fixed-gain adaptability, failing to meet stringent high-precision electric demands. To address these issues, this paper proposes a novel model-free sliding mode control strategy (MFITISMC–ADSTA–TISMO) integrating improved terminal integral sliding mode, adaptive super-twisting reaching law and improved Terminal Sliding Mode Observer (TISMO) for high-precision PMSM control. The core contributions are: 1). A novel PMSM ultra-local model incorporating state gains and lumped unknown disturbances is constructed, eliminating accurate motor model dependence and fundamentally eradicating model mismatch errors. 2). An improved terminal integral sliding mode surface with continuous smooth nonlinear functions is designed, which, combined with the adaptive super-twisting reaching law, ensures finite-time state convergence and mechanism-level chattering suppression. 3). An improved terminal sliding mode observer is developed to accurately estimate and compensate for total system disturbances in real time, significantly enhancing disturbance rejection under complex conditions. Experimental results demonstrate that the proposed strategy outperforms traditional methods in dynamic response, steady-state accuracy, multi-condition disturbance rejection and parameter robustness, validating its engineering value in high-performance electric drive control.

Scientific Reports
Central South University (CN)
National Natural Science Foundation of China
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Sensorless Control of Electric Motors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.