NDLI: Intelligent second-order sliding mode control for permanent magnet linear synchronous motor servo systems with robust compensator

Content Provider	IET Digital Library
Author	Zhao, Ximei Wang, Tianhe Jin, Hongyan
Abstract	In this study, an intelligent second-order sliding mode control (SMC) method combining second-order SMC (SOSMC) and recurrent radial basis function neural network (RRBFNN) applicable to the permanent magnet linear synchronous motor (PMLSM) is proposed to achieve high-performance servo control fields. On the basis of a dynamic model of PMLSM and the SMC theory, the chattering problem in SMC is weakened and the tracking accuracy is improved by the design of SOSMC. As for the boundary of the uncertainty factors is difficult to obtain, the optimal performance of SOSMC is hard to achieve, the RRBFNN uncertainty observer is introduced for estimating the value of the uncertainty factors. Owing to the strong learning ability, the network parameters can be trained online. Besides, a robust compensator is developed to suppress the uncertainties such as approximation error, optimal parameter vector and higher Taylor series for further improving the robustness. Moreover, the adaptive learning algorithms are obtained by using the Lyapunov theorem to guarantee the asymptotical stability of the system. The experiments demonstrate that the proposed scheme provides high performance dynamic characteristics and strong robustness to uncertainties.
Starting Page	1661
Ending Page	1671
Page Count	11
ISSN	17518660
Volume Number	14
e-ISSN	17518679
Issue Number	Issue 9, Sep (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-epa/14/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-epa.2020.0158
Journal	IET Electric Power Applications
Publisher Date	2020-05-12
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Asymptotic Stability Asymptotical Stability Chattering Problem Control of Electric Power System Control System Analysis Dynamic Modelling High Performance Dynamic Characteristic High-performance Servo Control Field Intelligent Second-order Learning in AI Linear Synchronous Motors Lyapunov Method Machine Control Mode Control Method Modelling And Identification Multivariable Control System Network Parameter Neurocontrol Neurocontrollers Nonlinear Control System Observers Optimal Parameter Vector Optimal Performance Permanent Magnet Linear Synchronous Motor Servo System Permanent Magnet Motors PMLSM Position Control Radial Basis Function Network Recurrent Neural Nets Recurrent Radial Basis Function Neural Network Robust Compensator Robust Control RRBFNN Uncertainty Observer Second-order SMC Servomechanisms Servomotors Simulation SMC Theory SOSMC Spatial Variables Control Stability in Control Theory Strong Learning Ability Strong Robustness Synchronous Machine Synthesis Method Tracking Accuracy Uncertainty Factors Variable Structure System
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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