Position control for permanent magnet synchronous motor based on neural network and terminal sliding mode control

Zhu, Weiyu; Chen, Dongbo; Du, Haibo; Wang, Xiangyu

doi:10.1177/0142331219893799

Cited by 22 publications

(23 citation statements)

References 31 publications

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“…Then, desired states and inputs are derived using ( 6), ( 7), (9), and (12). The the control inputs (12) are obtained with the optimal state feedback control (15) and (17).…”

Section: Closed-loop System Stability Analysismentioning

confidence: 99%

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Nonlinear Optimal Position Control with Observer for Position Tracking of Surfaced Mounded Permanent Magnet Synchronous Motors

Kim

2021

Applied Sciences

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Previous control methods were designed based on cascade structure and consist of position and current controllers for permanent magnet-synchronous motors (PMSMs). Thus, the structures of the previous methods are necessarily complex although the stability is guaranteed. Thus, the gain tuning is difficult to obtain for the desired control performance for the PMSMs. To overcome this problem, this paper proposes a nonlinear optimal position control method with an observer to improve the position tracking performance of PMSMs. The proposed method consists of a desired state generator, controller, and nonlinear observer. The desired states and inputs are derived using the PMSM model. Then, the state feedback controller is designed based on the whole tracking error dynamics including both mechanical and electrical dynamics. The nonlinear observer is designed to estimate the velocity and load torque. The closed-loop stability is proven using the input-to-state stability. The proposed method is not designed based on the cascade structure. Furthermore, the control and observer gains are chosen using an optimal control method to obtain the desired performance for the PMSMs. This approach simplifies the design process such that the control algorithm is suitable for real-time control. The performance of the proposed method is validated via simulations and experiments.

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“…Then, desired states and inputs are derived using ( 6), ( 7), (9), and (12). The the control inputs (12) are obtained with the optimal state feedback control (15) and (17).…”

Section: Closed-loop System Stability Analysismentioning

confidence: 99%

“…An output regulator based controller was proposed to reduce sideband harmonics for the PMSM [14]. A nonlinear control method using neural network and terminal sliding mode control was proposed for the PMSM [15]. Control methods using the combination of linear quadratic regulator (LQR) method and observer were developed [16,17].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Optimal Position Control with Observer for Position Tracking of Surfaced Mounded Permanent Magnet Synchronous Motors

Kim

2021

Applied Sciences

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“…MPC can predict and determine the future voltage vector to achieve the optimization of the cost function. The results are assessed by using the cost function penalizing the deviation from a given set point value to a hard constraint (Zhu et al, 2020). MPC transforms the control problem into an optimization problem, which provides great convenience for dealing with constraints and nonlinear models.…”

Section: Introductionmentioning

confidence: 99%

Explicit model predictive control of permanent magnet synchronous motors based on multi-point linearization

Guo

Pan

Liu

et al. 2021

Transactions of the Institute of Measurement and Control

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Permanent magnet synchronous motors (PMSMs) have been broadly applied in servo-drive applications. It is necessary to improve the performance of PMSM. An explicit controller designed for PMSM based on multi-point linearization is proposed to reduce the linearized model error caused by different running status of PMSM. The mathematical model of PMSM system in the synchronous rotating frame and the problem formulation are introduced at first. Then, the preliminaries about explicit model predictive control (MPC) algorithm are presented in this article. Based on this, the multi-point linearization model is created for explicit MPC controller design. Moreover, the block diagram of the proposed method for PMSM system is presented. Finally, the simulation results are provided to demonstrate that the proposed explicit MPC controller based on multi-point linearization achieves better performance than that based on traditional single-point linearization, but requires the same online computation time because of the offline optimization of explicit MPC.

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“…As a highly efficient robust control strategy, sliding mode control (SMC) has been extensively deployed in various practical implementations during the last decades (Chen et al, 2020a;Chu et al, 2018;Toshani and Farrokhi, 2019;Zhu et al, 2020). The rapidity and complete robustness are the significant merits of SMC (Chen et al, 2020b;Zhang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Disturbance estimator-based switching function for discrete-time sliding mode control systems with control saturation

Xiong

et al. 2021

Transactions of the Institute of Measurement and Control

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In this paper, a new disturbance estimator-based switching function (SF) is presented dedicated to discrete-time sliding mode control (DSMC) systems with disturbances and control saturation (CS). This SF is featured by an ( n+1)th-order disturbance estimator, which utilizes n+1 past disturbance terms to attain accurate disturbance rejection. Moreover, an auxiliary state is integrated into the SF to address the CS problem. One uniqueness of the developed method is that it is capable of achieving the ideal quasi-sliding mode and produces a zero-convergence error of the SF under the influence of disturbances and CS, which is rarely realized in DSMC methods. In addition, system states dynamics is rigorously analysed adopting the Lyapunov technique. The feasibility and virtue of the designed results are verified by a numerical example.

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Position control for permanent magnet synchronous motor based on neural network and terminal sliding mode control

Cited by 22 publications

References 31 publications

Nonlinear Optimal Position Control with Observer for Position Tracking of Surfaced Mounded Permanent Magnet Synchronous Motors

Nonlinear Optimal Position Control with Observer for Position Tracking of Surfaced Mounded Permanent Magnet Synchronous Motors

Explicit model predictive control of permanent magnet synchronous motors based on multi-point linearization

Disturbance estimator-based switching function for discrete-time sliding mode control systems with control saturation

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