文献类型：期刊文献

英文题名：Self-Triggered Sliding Mode Control for Networked PMSM Speed Regulation System: A PSO-Optimized Super-Twisting Algorithm

作者：Song, Jun[1,2];Zheng, Wei Xing[2];Niu, Yugang[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Western Sydney Univ, Sch Comp Data & Math Sci, Sydney, NSW 2751, Australia

年份：2022

卷号：69

期号：1

起止页码：763

外文期刊名：IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

收录：;EI(收录号：20210409830078);WOS:【SCI-EXPANDED(收录号:WOS:000704120200075)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61903143 and Grant 62073139, in part by the Shanghai Chenguang Program under Grant 19CG33, in part by the Shanghai Sailing Program under Grant 19YF1412100, in part by the 111 Project (B17017) from China, and in part by the Australian Research Council under Grant DP120104986.

语种：英文

外文关键词：Regulation; Perturbation methods; Convergence; Optimization; Stators; Particle swarm optimization; Trajectory; Particle swarm optimization (PSO); permanent magnet synchronous motor (PMSM); self-triggered mechanism; super-twisting algorithm (STA)

摘要：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.