Discrete-time sliding mode controller based on backstepping disturbance compensation for robust current control of PMSM drives

Gabbi, Thieli Smidt; Araujo, Marcelo Back de; Rocha, Lucas Rossato; Scalcon, Filipe Pinarello; Gründling, Hilton Abílio; Vieira, Rodrigo Padilha

doi:10.1016/j.isatra.2021.10.032

Cited by 15 publications

(1 citation statement)

References 35 publications

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“…In the above-listed control algorithms, backstepping has its promising superiorities in constructing robust or adaptive controllers owing to its ease of integration with intelligent estimators (Yu et al, 2012; You et al, 2021). Therefore, many backstepping control efforts have been explored in the PMSM (Gabbi et al, 2021; Lin et al, 2017). However, the “explosion of complexity” caused by the classical backstepping control may degrade the operation of the system.…”

Section: Introductionmentioning

confidence: 99%

Neural adaptive finite-time dynamic surface control for the PMSM system with time delays and asymmetric time-varying output constraint

Zhang

et al. 2022

Journal of Vibration and Control

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This paper presents a neural adaptive finite-time dynamic surface control for the permanent magnet synchronous motor system with time delays and asymmetric time-varying output constraint. The core challenge is how to address the time delays and asymmetric output constraint when designing a finite-time control scheme. Given this, a proper Lyapunov–Krasovskii functional is introduced to address time delays, and a nonlinear transformation function is considered to convert the output-constrained problem into an unconstrained one. Then, a neural adaptive finite-time dynamic surface control approach is devised in the finite-time backstepping framework, which applies neural networks to estimate the unknown nonlinear functions and introduces first-order filters to solve the “explosion of complexity” problems. Furthermore, it is demonstrated that all the signals of the resulting system are finite-time stable and the tracking error converges to a neighborhood of origin in finite time without violating the output constraint. Finally, the simulation results show that the integration of squared error results, the integral of time and absolute error results as well as the integration of absolute value error results of the proposed scheme is smaller than the tested scheme by 0.3458 [Formula: see text], 22.2977 [Formula: see text], and 2.2513 [Formula: see text], respectively, when the time delays are considered. It further elucidates the availability and superiority of the developed method.

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