Self-triggered sliding mode control for networked PMSM speed regulation system : a PSO-optimized super-twisting algorithm

Jun Song, Wei Xing Zheng, Yugang Niu

Research output: Contribution to journalArticlepeer-review

71 Citations (Scopus)

Abstract

This article is concerned with the design of a super-twisting algorithm (STA) based sliding mode controller for permanent magnet synchronous motor (PMSM) speed regulation system under the self-triggered mechanism. By using the strict Lyapunov function approach, it is shown that the tracking error converges to an ultimate domain within the finite-time sense under the proposed self-triggered STA. A feasible self-triggered strategy is designed for both cases with and without external perturbation. Moreover, a nonlinear optimization problem is formulated in terms of the tradeoff between the ultimate domain and the communication burden. The optimized STA gains are obtained by solving the above-formulated optimization problem via a particle swarm optimization algorithm. Finally, the applicability of the proposed self-triggered STA for PMSM is verified by simulation and experiment results.

Original languageEnglish
Pages (from-to)763-773
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Volume69
Issue number1
DOIs
Publication statusPublished - 1 Jan 2022

Bibliographical note

Publisher Copyright:
© 1982-2012 IEEE.

Fingerprint

Dive into the research topics of 'Self-triggered sliding mode control for networked PMSM speed regulation system : a PSO-optimized super-twisting algorithm'. Together they form a unique fingerprint.

Cite this