Model-Free Control Using Improved Smoothing Extended State Observer and Super-Twisting Nonlinear Sliding Mode Control for PMSM Drives

Peng Gao,Guangming Zhang,Xiaodong Lv

doi:10.3390/en14040922

Abstract

This paper proposes a novel model-free super-twisting nonlinear sliding mode control (MFSTNLSMC) strategy with an improved smoothing extended state observer (SESO) for permanent magnet synchronous motor (PMSM) drives. First of all, the improved SESO is introduced to estimate the unknown term of the PMSM ultra-local model. Secondly, a novel nonlinear sliding mode surface (NLSMS) is designed, which can effectively overcome the disadvantages of simple and rough signal processing of the conventional linear sliding mode surface. At the same time, a super-twisting (ST) structure is chosen to suppress the chattering phenomenon and improve system robustness. Then, the Lyapunov stability theorem is used to prove the stability of the proposed control algorithm. Finally, both comparative simulations and experimental demonstrations verify the excellent speed tracking performance and robustness of the proposed control strategy.

Highlights

As the permanent magnet synchronous motor (PMSM) has low energy consumption, reliable operation, and simple structure, it has been widely used in coal conveyor systems [1], mine traction electric locomotives [2], electric vehicles [3,4], water pumping applications [5] and so on
During the past few decades, various sliding mode controller (SMC) strategies have been widely used in the PMSM speed control system such as fractional order SMC [11,12], integral
Aimed to further check on the effectiveness of the proposed MFSTNLSMC strategy, a cSPACE (Control signal process and control engineering) based PMSM speed control experimental platform was applied in this paper

Summary

Introduction

As the permanent magnet synchronous motor (PMSM) has low energy consumption, reliable operation, and simple structure, it has been widely used in coal conveyor systems [1], mine traction electric locomotives [2], electric vehicles [3,4], water pumping applications [5] and so on. The PMSM dynamic model has the characteristics of coupling and is multivariable. It is difficult for the traditional model-based control strategy to meet the control requirements. Because of its simple structure and high estimation efficiency, the nonlinear ESO has been widely used in many applications such as welding robot [7], linear system with incipient fault [8], aerial inertially stabilized platform [9], teleoperated robotic system [10] and so on. During the past few decades, various SMC strategies have been widely used in the PMSM speed control system such as fractional order SMC [11,12], integral

Methods

Results

Conclusion