Robust Continuous Model Predictive Speed and Current Control for PMSM With Adaptive Integral Sliding-Mode Approach

Li, Zheng; Ke, Dongliang; Li, Jiaxiang; Zhang, Wei

doi:10.1109/tpel.2021.3086636

Cited by 66 publications

(29 citation statements)

References 23 publications

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“…The term 𝑑 involves, d=d 1 ‖x‖+d 2 where d 1 ≤∆ 1 besides d 2 ≤∆ 2 Super twisting multivariable control u is given below (6) where k i >0,i=1,2,3,4 are the constant parameters chosen in way that the aforementioned controller would be able to stabilize the MIMO structure in finitetime. Putting 𝑢 as of ( 6) to (5), we can write (7) By specifying 𝜂 = 𝑣 + d 2 , we get (7) (8) State variables finite-time convergence 𝑥, 𝑥̇ as well 𝜂 are to be achieved and keep zero for subsequent time by k 1 , k 2 , k 3 , k 4 . As of eq (8) when states touches origin we get, η=v+d 2 =0…”

Section: Super Twisting Multivariable (Stm) Algorithmmentioning

confidence: 99%

“…Thereafter, the Lyapunov scheme was introduced for proofs by [6]. From the several SMC approaches, integral SMC [7][8][9][10][11][12][13][14]17], may be readily integrated other new latest control strategies like proportional integral derivative (PID) control, linear feedback control, model predictive control, optimum control and so on, while retaining their features. As a result, ISMC may be described as bridge in between other control methods plus sliding mode which has greater robustness than other existing control systems.…”

Section: Introductionmentioning

confidence: 99%

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Design of Super Twisting Integral Sliding Mode Control for Industrial Robot Manipulator

Gambhire

Kishore²,

Kumar

et al. 2022

Int. j. electr. comput. eng. syst. (Online)

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In the present work, integral sliding mode based continuous control algorithm is extended to multi input multi output system. The typical integral sliding mode control (ISMC) contains nominal control with discontinuous feedback control due to which overall control becomes discontinuous in nature. The proposed controller is a fusion of two continuous terms and one of which is able to handle, estimate and reject the disturbance successfully. A proposed robust ISMC technique is applied for industrial robot manipulators which utilizes interactive manipulation activity. Here, robust position tracking control obtained via ISMC principle for two link IRM scheme influenced by parametric uncertainties and external disturbances. The proposed ISMC design replaces the discontinuous part by continuous control, which super twisting control is able to handle the disturbance rejection completely. The effectiveness of the proposed control technique is tested under uncertain conditions and comparison study with other controllers has been done. The simulation result shows that the tracking error is effectively minimized by the proposed technique in presence of uncertain conditions.

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Section: Super Twisting Multivariable (Stm) Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design of Super Twisting Integral Sliding Mode Control for Industrial Robot Manipulator

Gambhire

Kishore²,

Kumar

et al. 2022

Int. j. electr. comput. eng. syst. (Online)

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show abstract

“…During the last decades, the investigators have proposed plenty of crucial control approaches to fulfill the higher requirement of the PMSM control systems. The primary control methods are sliding mode control [3][4][5][6][7], adaptive control [8][9][10][11][12], backstepping control [13][14][15][16][17], and so on.…”

Section: Introductionmentioning

confidence: 99%

Disturbance‐observer‐based adaptive finite‐time dynamic surface control for PMSM with time‐varying asymmetric output constraint

Zhang

et al. 2023

Asian Journal of Control

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This article presents a disturbance‐observer‐based adaptive finite‐time dynamic surface control scheme, capable of guaranteeing transient behavior for the PMSM with arbitrary asymmetric time‐varying output constraint and unmatched external disturbance. The major challenge of this paper is devising efficient strategies to tackle the nonsymmetric output restraints with arbitrary characteristics and unmatched external perturbation for the system under the finite‐time backstepping framework. Given this, a nonlinear transformation function is adopted to coordinate from the output‐constrained dynamic model to an uncontained one, and a finite‐time disturbance observer is introduced to evaluate the unmatched external perturbation. Then, a dynamic surface control approach having adaptive properties for PMSM is conceived by combing a neural network to evaluate the nonlinear functions and a first‐order filter to handle the “explosion of complexity.” Additionally, it is proved that the signals in the closed‐loop system can narrow down to a bounded region and the tracking error can merge in a limited time to tiny vicinity of zero by employing a fast finite‐time stability principle. Eventually, simulation cases and contrast results reveal the tracking performance and immunity to the disturbance of the devised controller.

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“…Even though the model of motor is usually considered timeinvariant, all parameters do not remain the same, and these differences lead to the prediction errors [7]. Due to this parameter mismatch affecting the controller's output, the methods to increase the robustness are being developed [8]- [10]. Apart from robustness, the other common approach to mitigate the effect of parameter mismatch is adaptivity.…”

Section: Introductionmentioning

confidence: 99%

Adaptivity Schemes for Model Predictive Speed Control of PMSM

Kozubík

Václavek

Merino

2022

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society

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Model predictive control is a popular research topic in the field of motor control. Its direct way of implementing constraints and nonlinearities makes MPC a potential alternative to standard motor control approaches. On the other hand, the control algorithm's dependency on the motor model's precision can make it tricky. Especially when the parameters of the controlled machine change over time. This paper presents a possible solution to a stated problem based on the model adaptivity. Firstly, the connection between experimental data and the parameters change is analyzed. Then, adaptivity schemes are presented. After that, the simulation experiment evaluates the performance of the proposed schemes.

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Robust Continuous Model Predictive Speed and Current Control for PMSM With Adaptive Integral Sliding-Mode Approach

Cited by 66 publications

References 23 publications

Design of Super Twisting Integral Sliding Mode Control for Industrial Robot Manipulator

Design of Super Twisting Integral Sliding Mode Control for Industrial Robot Manipulator

Disturbance‐observer‐based adaptive finite‐time dynamic surface control for PMSM with time‐varying asymmetric output constraint

Adaptivity Schemes for Model Predictive Speed Control of PMSM

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