PMSM speed control based on intelligent sliding mode technique

Tavoosi, Jafar

doi:10.1108/compel-04-2020-0137

Cited by 12 publications

(6 citation statements)

References 28 publications

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“…In recent years, several nonlinear control methods have been applied to solve the classical linear PI control problem and to control the Permanent Magnet Synchronous Motor (PMSM) in various complex situations. These methods include fuzzy control [1], adaptive control [2], predictive control [3], sliding mode control (SMC) [4][5][6][7][8][9], and robust control. These methods have improved the stability of the PMSM system from different aspects.…”

Section: Introductionmentioning

confidence: 99%

“…In [5], a predictive control based on SMC is proposed to enhance the velocity robustness and current tracking accuracy of PMSM systems. In [6], researchers designed a novel radial basis function recursive network (RBFN) to approximate the unknown nonlinear functions in the PMSM dynamics. In [7], a memoryless, memory-based sliding integral mode controller is proposed and applied to the control of motor control.…”

Section: Introductionmentioning

confidence: 99%

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PMSM Sliding Mode Control Based on Improved Reaching Law

Wang

Jiang

et al. 2023

Preprint

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This paper proposes a novel adaptive reaching law-based sliding mode control (SMC) method for maintaining favorable velocity control performance of permanent magnet synchronous motors (PMSMs) under internal and external perturbations. A new sliding mode reaching law (NSMRL) is designed, which contains adaptive terms and state variables of the sliding mode surface function. This augmented reaching law decreases the chatter of the control system and increases the rate at which the state variables of the system reach the sliding mode surface. Additionally, a Luenberger observer load torque (LOLT) is designed to observe the external load and provide feedback to the velocity controller, reducing the impact of load disturbances and improving the jamming performance of the controller. Simulation experiments confirm that NSMRL reduces buffeting, decreases overshoot, and shortens response time, demonstrating its advantages in PMSM control.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

PMSM Sliding Mode Control Based on Improved Reaching Law

Wang

Jiang

et al. 2023

Preprint

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“…Although model predictive control and active disturbance rejection control can improve the speed control accuracy and dynamic performance of the system [9][10][11][12], the algorithms are complex and not easy to implement quickly. In [13], a backstepping sliding mode control based on a recurrent radial basis function network (RBFN) for a PMSM is presented, with a novel combination of the backstepping method and sliding mode control, eliminating the chattering effectively without losing the precision. In [14], an online PID parameter adjustment control, combining model predictive control and on-line fuzzy rule adjustment, is proposed.…”

Section: Introductionmentioning

confidence: 99%

Linear Golden Section Speed Adaptive Control of Permanent Magnet Synchronous Motor Based on Model Design

et al. 2022

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Permanent magnet synchronous motor (PMSM) is a multi-variable, strongly coupled, nonlinear complex system. It is usually difficult to establish an accurate mathematical model, and the introduction of new complex algorithms will increase the difficulty of embedded code development. In order to solve this problem, we establish the characteristic model of permanent magnet synchronous motor in this paper, and the speed control scheme of the linear golden-section adaptive control and integral compensation, which is adopted. Finally, using the model-based design (MBD) method, how to build the simulink embedded code automatic generation model is introduced in detail, and then we complete the PMSM speed control physical verification experiment. Simulation and experimental results show that compared with traditional proportional-integral-derivative (PID) control, the speed control accuracy of PMSM is improved about 3.8 times. Meanwhile, the development method based on the model design can increase the PMSM control system physical verification, and then improve the development efficiency.

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“…Nowadays, combined fuzzy neural methods with sliding mode control [4,5], inverse control [6], robust control [7], H ∞ [8], adaptive estimator [9], etc. to control the speed and position of the permanent magnet synchronous motor are widely used.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of a Novel Intelligent Strategy for the Permanent Magnet Synchronous Motor Emulation

2022

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In this paper, an intelligent neural network-based controller is designed and implemented to control the speed of a permanent magnet synchronous motor (PMSM). First, the exact mathematical model of PMSM is presented, and then, by designing a controller, we apply the wind turbine emulation challenges. The designed controller for the first time is implemented on a Arm Cortex-M microcontroller and tested on a laboratory PMSM. Since online learning neural network on a chip requires a strong processor, high memory, and convergence guarantee, this article uses the offline method. In this method, first, for different work points, the neural network is trained by local controllers, and then, the trained network is implemented on the chip and used. Uncertainty in the parameters and the effect of load torque as challenges of control systems are applied in the proposed method, and a comparison with other methods is performed in the implementation results section.

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PMSM speed control based on intelligent sliding mode technique

Cited by 12 publications

References 28 publications

PMSM Sliding Mode Control Based on Improved Reaching Law

PMSM Sliding Mode Control Based on Improved Reaching Law

Linear Golden Section Speed Adaptive Control of Permanent Magnet Synchronous Motor Based on Model Design

Design and Implementation of a Novel Intelligent Strategy for the Permanent Magnet Synchronous Motor Emulation

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