Modular neural dynamic surface control for position tracking of permanent magnet synchronous motor subject to unknown uncertainties

Cong, Siming; Liu, Lu; Peng, Zhouhua; Zhang, Yibo

doi:10.1016/j.neucom.2019.06.017

Cited by 10 publications

(16 citation statements)

References 37 publications

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“…Experiment results are shown in Figs. [11][12][13][14][15][16][17][18][19][20][21][22]. Specifically, Fig.…”

Section: B Experiments Resultsmentioning

confidence: 99%

“…IPMSM is a complicated system of high-nonlinearities, strong-coupling and multi-variables, and its parameters are very sensitive to environment. In order to achieve high control performance of IPMSM, such as fast response, high precision, and strong anti-disturbance capacity, various control strategies are proposed including proportional integral (PI) control [4], [5], [6], [7], [8], neural network (NN) control [9], [10], [11], [12], [13], [14], fuzzy control [15], [16], [17], [3], [18], sliding mode control [19], [20], [21], [22], [23], predictive control [24], [25], [26], [27], dynamic surface control(DSC) [10], [28], [29], [30], [13] and extended-state-observer-based control [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], etc. Specifically, in [3], a discrete-time fuzzy position tracking controller is designed via backstepping approach to overcome the problem of coupling nonlinearity in the IPMSM drive system.…”

Section: Introductionmentioning

confidence: 99%

“…In [29], a fuzzy finite-time DSC method for PMSM is proposed, where the log-type barrier Lyapunov function is established to constrain the stator current, angular speed and other state variables in the predefined compact sets. In [13], a predictor-based neural DSC method is proposed for PMSM, which can identify the system dynamics more smoothly and quickly without causing high-frequency oscillations in learning process and control signals. However, it is worthwhile mentioning that most existing control methods for PMSMs are based on the state feedback.…”

Section: Introductionmentioning

confidence: 99%

“…Finally, in the presence of position measurements only, the controller is able to obtain a desired anti-disturbance performance. The main features are stated as follows: (i) Compared with the state-feedback method in [13], [21], [43], where both the position and the velocity information are used in the design, the output-feedback method only needs the motor position information. (ii) Compared with the linear ESO-based control method [33], the gain of the linear function may be larger in order to improve the observation accuracy.…”

Section: Introductionmentioning

confidence: 99%

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Anti-Disturbance Dynamic Surface Control for Position Tracking of Interior Permanent Magnet Synchronous Motor Based on Nonlinear Extended State Observer

et al. 2021

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In this paper, an anti-disturbance output feedback dynamic surface control (DSC) method is proposed for the position tracking of interior permanent magnet synchronous motor subject to unknown nonlinearities and time-varying disturbances. Specifically, a nonlinear extended-state-observer (NLESO) based on exponential functions is designed to estimate the total disturbance composed of system uncertainties and external disturbances. Then, by compensating for the total disturbance via the NLESO, an anti-disturbance output feedback law is designed based on the DSC approach. The salient features of the proposed approach is twofold. First, the total uncertainty including internal and external disturbances can be accurately estimated by an NLESO in real time. Second, the desired anti-disturbance performance of the servo control system can be achieved regardless of the position measurement only. The stability of the closed-loop control system is proved by using the cascade theory and input-to-state stability theory. Both simulation and experiment results are conducted to illustrate the effectiveness of the proposed control method.

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“…Experiment results are shown in Figs. [11][12][13][14][15][16][17][18][19][20][21][22]. Specifically, Fig.…”

Section: B Experiments Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Anti-Disturbance Dynamic Surface Control for Position Tracking of Interior Permanent Magnet Synchronous Motor Based on Nonlinear Extended State Observer

et al. 2021

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show abstract

“…Many articles about improved DSC method has been concerned. [43] proposed a novel modular neural dynamic surface control method for the position tracking control of PMSMs. A second-order nonlinear tracking differentiator (NLTD) instead of a first-order filter is used to extract the time derivatives of virtual control law, which makes the derivative of virtual control input more accurate.…”

Section: Introductionmentioning

confidence: 99%

Improved Adaptive Dynamic Surface Control for a Class of Uncertain Nonlinear Systems

et al. 2020

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An improved dynamic surface control (IDSC) approach is presented for a class of strictfeedback nonlinear systems with unknown functions. The proposed method makes the state errors get rid of the influence of first-order filters, which simplifies the design of control. By employing neural networks to account for system uncertainties, the virtual control signal of the IDSC is directly used to construct the state error instead of the signal generated by the first-order filter in the dynamic surface control (DSC) method. The stability of the method is proved by Lyapunov stability theory, and the semi-global uniform ultimate boundedness of all signals in the closed-loop system is guaranteed. Simulation results demonstrate the IDSC method has better tracking performance and stability than traditional DSC method.INDEX TERMS Neural networks, improved dynamic surface control (IDSC), strict-feedback nonlinear system, virtual control signal.

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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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Modular neural dynamic surface control for position tracking of permanent magnet synchronous motor subject to unknown uncertainties

Cited by 10 publications

References 37 publications

Anti-Disturbance Dynamic Surface Control for Position Tracking of Interior Permanent Magnet Synchronous Motor Based on Nonlinear Extended State Observer

Anti-Disturbance Dynamic Surface Control for Position Tracking of Interior Permanent Magnet Synchronous Motor Based on Nonlinear Extended State Observer

Improved Adaptive Dynamic Surface Control for a Class of Uncertain Nonlinear Systems

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

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