Research on chaos control of permanent magnet synchronous motor based on the synthetical sliding mode control of inverse system decoupling

Zhang, Rongyun; Gong, Chenglong; Shi, Peicheng; Zhao, Lian; Changsheng, Zheng

doi:10.1177/1077546320936499

Cited by 13 publications

(12 citation statements)

References 15 publications

(11 reference statements)

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“…To train the fuzzy neural network, a combination of the least-squares method is used to update the parameters of the fourth layer (p i , q i , r i ), and the error propagation method is used to update the parameters of the Gaussian membership function (σ k i , m k i ). In the least-squares method, it is assumed that the network output is obtained as follows [6]:…”

Section: Fuzzy Neural Networkmentioning

confidence: 99%

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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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Section: Fuzzy Neural Networkmentioning

confidence: 99%

“…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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“…Permanent magnet synchronous motors have low losses [1] , high power factor [2] , and high efficiency [3] . But it is a typical nonlinear, multivariable coupled system that can cause the motor to exhibit chaotic behavior under specific parameters, and reduce the operational quality of the PMSM system [4] .…”

Section: Introductionmentioning

confidence: 99%

Dual-parameter collaborative intelligent optimal control of chaotic motion of permanent magnet synchronous motor

Qiu

Wei

et al. 2023

Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023)

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Aiming at the chaos control of permanent magnet synchronous motor, a dual-parameter collaborative intelligent optimal control method based on GWO-RBFNN was proposed. Starting from the perspective that the controller can automatically search for the expected motion state, the distance between two points on the Poincaré cross section is selected as the controller input. And considering the coupling effect of system parameters on the dynamic behavior of the system, a dualparameter cooperative controller is designed based on radial basis function neural network (RBFNN); Grey Wolf Optimization (GWO) algorithm is used to optimize the selection of controller parameters; By slightly adjusting the two controllable parameters of the system, the chaotic motion of the PMSM system is controlled to the expected motion state. In the simulation study, compared with the single-parameter intelligent optimization control method based on GWO-RBFNN, the results show that although both methods can achieve chaotic motion control, the control speed of the dual-parameter collaborative intelligent optimization control method based on GWO-RBFNN is faster and overshoot is smaller.

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“…Interior permanent magnet synchronous motor (IPMSM) is broadly used in various industrial fields due to its simple structure, high efficiency, and good dynamic response. 1,2 However, it is a difficult problem to control the IPMSM to achieve satisfactory performance because its dynamics are usually coupled, highly nonlinear, and multivariable; and sensitive to parameter perturbations and load disturbances. 3 The conventional linear controllers such as proportional-integral (PI), proportional-integral-derivative (PID) are commonly used because of their simple implementation and applicability in most industrial control processes.…”

Section: Introductionmentioning

confidence: 99%

Modified backstepping control of IPMSM: Experimental tests

Nadji

Benaicha

Moreau

2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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The purpose of this paper is to propose a new control technique for an interior permanent magnet synchronous motor that has been designed using a modified integral backstepping controller. This architecture consists of a nonlinear backstepping control scheme to achieve the purpose of speed tracking. Then the nonlinear controller based on the backstepping control scheme with the introduction of integral actions is designed for the IPMSM drive system. The suggested controller is not only designed to stabilize the interior permanent magnet synchronous motor system, but also to ensure that the speed tracking error converges asymptotically to zero in the existence of system uncertainties and external disturbances. The advantage of the suggested approach is that the proposed controller guarantees good tracking performance, reduces steady-state errors, robustness against all parameter uncertainties, and load torque disturbances in the interior permanent magnet synchronous motor system. A new speed control scheme for the design of the interior permanent magnet synchronous motor is being developed in this work. To show the feasibility of the suggested approach, the experiment is carried out with a real-time interface based on dSPACE. A comparison with the proportional-integral controller has been made. The results prove that the proposed backstepping controller has a rapid transient response and strong robustness for all disturbances under different conditions.

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Research on chaos control of permanent magnet synchronous motor based on the synthetical sliding mode control of inverse system decoupling

Cited by 13 publications

References 15 publications

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

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

Dual-parameter collaborative intelligent optimal control of chaotic motion of permanent magnet synchronous motor

Modified backstepping control of IPMSM: Experimental tests

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