Adaptive Nonsingular Finite-Time Terminal Sliding Mode Control for Synchronous Reluctance Motor

Ren, Linjie; Lin, Guobin; Zhao, Yuanzhe; Liao, Zhiming; Peng, Fei

doi:10.1109/access.2021.3068745

Cited by 14 publications

(9 citation statements)

References 30 publications

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“…The TERL is utilized to propose the ASMCRL, proposed reaching law updates according to system state and fluctuations. Appraising that terminal attractor | s | β sgn ( s ) term smoothness near the sliding manifold [ 20 ], the ASMCRL is given as …”

Section: Design Of Sliding Mode Control Reaching Lawmentioning

confidence: 99%

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Finite-time robust speed control of synchronous reluctance motor using disturbance rejection sliding mode control with advanced reaching law

Nasim,

Bhatti,

Farhan

et al. 2023

PLoS ONE

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In recent years, there has been a significant focus on synchronous reluctance motors (SynRM) owing to their impressive efficiency and absence of magnetic material. Although the SynRM shows great potential for use in electric vehicles, its widespread adoption is limited by unmodeled dynamics and external disturbances. Moreover, the uncertainty factor significantly restricts SynRM’s peak efficiency and superior control performance, leading to an unjustifiable current loop reference command. To address these issues, this work presents various new research contributions which focus on the robust control of SynRM to optimize performance through the novel reaching law-based sliding mode control. Initially, a novel advanced sliding mode control reaching law (ASMCRL) with adaptive gain is proposed, to enhance the acceleration of the system state reaching the sliding surface. After that, an extended state observer (ESO) is designed to estimate and compensate for the overall disturbances of the system. Finally, the ASMCRL and ESO are integrated to design two nonlinear controllers namely, the disturbance-rejection sliding mode controller (DRSMC) and the disturbance-rejection sliding mode speed regulator (DRSMSR) for SynRM. The proposed DRSMSR eliminates the steady-state error and eradicates inherent chattering in DRSMC. Moreover, this yields a system trajectory that converges to a predetermined proximity of the sliding surface, irrespective of any lumped disturbances. The steady-state error of DRSMSR is less as compared to DRSMC. Furthermore, the speed response of this technique is 22.62% faster as compared to the state-of-the-art finite-time adaptive terminal sliding mode control. Additionally, the asymptotic stability of the proposed system is validated using Lyapunov’s theorem. Thus the experimental results demonstrate the effectiveness and robustness of the proposed approach.

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Section: Design Of Sliding Mode Control Reaching Lawmentioning

confidence: 99%

“…However, the speed response is slow and error increases with the external load increase. In [ 20 ], a finite time terminal SMC for SynRM has been proposed, which has a robust control response against parameter variations. An observer is designed to overcome the disturbances, and a new-reaching law is proposed to reduce chattering.…”

Section: Introductionmentioning

confidence: 99%

Finite-time robust speed control of synchronous reluctance motor using disturbance rejection sliding mode control with advanced reaching law

Nasim,

Bhatti,

Farhan

et al. 2023

PLoS ONE

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“…In some studies, scholars improved the reaching law of sliding mode to reduce chattering and improve the convergence of the controller [9,10]. In one study, a novel nonsingular terminal sliding mode control (NTSMC) is designed to weaken the chattering in [11]. Due to the convergence property of the fractional-order algorithm, it is applied in the design of the SMC to reduce the chattering around the sliding surface and to enhance the robustness of the controller [12,13].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Super-Twisting Sliding Mode Control of Active Power Filter Using Interval Type-2-Fuzzy Neural Networks

2023

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Aiming at the unknown uncertainty of an active power filter system in practical operation, combining the advantages of self-feedback structure, interval type-2 fuzzy neural network, and super-twisting sliding mode, an adaptive super-twisting sliding mode control method of interval type-2 fuzzy neural network with self-feedback recursive structure (IT2FNN-SFR STSMC) is proposed in this paper. IT2FNN has an uncertain membership function, which can enhance the nonlinear ability and robustness of the network. The historical information will be stored and utilized by the self-feedback recursive structure (SFR) at runtime. Therefore, the novel IT2FNN-SFR is designed to improve the dynamic approximation effect of the neural network and reduce the dependence of the controller on the actual mathematical model. The adaptive rate of each weight of the neural network is designed by the Lyapunov method and gradient descent (GD) algorithm to ensure the convergence and stability of the system. Super-twisting sliding mode control (STSMC) has strong robustness, which can effectively reduce system chattering, and improve control accuracy and system performance. The gain of the integral term in the STSMC is set as a constant, and the other gain is changed adaptively whose adaptive rate is deduced through the stability proof of the neural network, which greatly reduces the difficulty of parameter adjustment. The harmonic suppression ability of the designed control strategy is verified by simulation experiments.

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“…This urgently requires the robot to converge quickly to ensure that MRMs stably reaches the target position before performing the operation task, so as to improve the operation accuracy. Therefore, the terminal sliding mode controller (TSMC) has been developed to allow the control system to converge within finite time [9][10][11][12][13]. Different from the traditional SMC, the nonlinear sliding hyperplane is adopted in TSMC to ensure that the system state achieves rapid finite time convergence in the sliding phase [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

A Novel Decentralized Fixed-time Tracking Control for Modular Robot Manipulators: Theoretical and Experimental Verification

2023

Int. J. Control Autom. Syst.

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This paper proposes a novel decentralized fixed-time tracking control approach, which realizes the advantages of modular robot manipulators (MRMs) with fixed-time convergence, strong robustness, and high tracking performance. First, to estimate the total uncertainty of MRMs, the fixed-time disturbance observer based on the extended state is developed. Then, combined with the disturbance observer, a novel decentralized control method based on fixed-time control strategy was developed to achieve the global fixed-time convergence of MRMs. And, stability analysis based on Lyapunov is used to obtain the fixed-time stability and convergence time of MRMs. Finally, numerical analysis and experiment respectively verify the excellent tracking ability of the proposed decentralized fixed-time tracking control algorithm.

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Adaptive Nonsingular Finite-Time Terminal Sliding Mode Control for Synchronous Reluctance Motor

Cited by 14 publications

References 30 publications

Finite-time robust speed control of synchronous reluctance motor using disturbance rejection sliding mode control with advanced reaching law

Finite-time robust speed control of synchronous reluctance motor using disturbance rejection sliding mode control with advanced reaching law

Adaptive Super-Twisting Sliding Mode Control of Active Power Filter Using Interval Type-2-Fuzzy Neural Networks

A Novel Decentralized Fixed-time Tracking Control for Modular Robot Manipulators: Theoretical and Experimental Verification

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