PSO-Based PI Controller for Speed Sensorless Control of PMSM

Nazelan, A. M.; Osman, Muhammad Khusairi; Samat, Ahmad Asri Abd; Salim, Nur Ashida

doi:10.1088/1742-6596/1019/1/012027

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…The current observer-based control strategy can overcome the effect of interference on system robustness, but it increases the complexity of the controller design, and sometimes affects system stability. In recent years, researchers have proposed new current control strategies to solve specific problems [16]. A current control strategy based on the optimization of the second-order terminal sliding mode is proposed [23], which effectively removes vibrations and improves the robustness of the current control.…”

Section: Predictive Current Control (Pcc)mentioning

confidence: 99%

“…strategies to solve specific problems [16]. A current control strategy based on the optimization of the second-order terminal sliding mode is proposed [23], which effectively removes vibrations and improves the robustness of the current control.…”

Section: Predictive Current Control (Pcc)mentioning

confidence: 99%

“…In speed current cascading control, the relationship between the output speed and the four-axis reference current is usually defined by the first-order model. However, given that closed-loop performance may decline due to the disappearance of the relative difference in control cycles between the two loops, a secondorder model relationship is also proposed [8,16]. For high-speed PMSM applications, the integration speed and current controller have been used to address the nonlinear coupling between speed and current.…”

Section: Introductionmentioning

confidence: 99%

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Critical Review on Robust Speed Control Techniques for Permanent Magnet Synchronous Motor (PMSM) Speed Regulation

2022

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The permanent magnet synchronous motor (PMSM) is a highly efficient energy saving machine. Due to its simple structural characteristics, good heat radiation capability, and high efficiency, PMSMs are gradually replacing AC induction motors in many industrial applications. The PMSM has a nonlinear system and lies on parameters that differ over time with complex high-class dynamics. To achieve the excessive performance operation of a PMSM, it essentially needs a speed controller for providing accurate speed tracking, slight overshoot, and robust disturbance repulsion. Therefore, this article provides an overview of different robust control techniques for PMSMs and reviews the implementation of a speed controller. In view of the uncertainty factors, such as parameter perturbation and load disturbance, the H∞ robust control strategy is mainly reviewed based on the traditional control techniques, i.e., robust H∞ sliding mode controller (SMC), and H∞ robust current controller based on Hamilton–Jacobi Inequality (HJI) theory. Based on comparative analysis, this review simplifies the development trend of different control technologies used for a PMSM speed regulation system.

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Section: Predictive Current Control (Pcc)mentioning

confidence: 99%

Section: Predictive Current Control (Pcc)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Critical Review on Robust Speed Control Techniques for Permanent Magnet Synchronous Motor (PMSM) Speed Regulation

2022

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“…Regarding previous works for optimizing PID controllers, the PSO is faster than GA when looking closely at idealistic solutions in case of does not require a detailed mathematical description of the process for formulating the Objective Function (OF) to optimize proportional gains, where the drawbacks of PSO are the lack of certainty that an optimal solution will be found and even the high computational costs associated with FF [66][67][68]. Consequently, standard PSOs often fail to solve these complex problems because they easily get stuck in local optima and converge slowly [69].…”

Section: Introductionmentioning

confidence: 99%

Perspective Chapter: Fabulous Design Speed Industrial Robotic Arm

Alkhafaji¹

2023

Human-Robot Interaction - Perspectives and Applications

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This chapter focuses on the design of a handling 5 Degree of freedom (DOF) robot arm model for industrial application. Optimal trajectory planning of industrial robots in the assembly line is a key topic to boost productivity in a variety of manufacturing activities. The aim is to improve the speed performance using multi techniques starting from estimating the transfer function of each manipulated joint, then designing the controller for each DOF reached to modeling arm motion. The designed model has been developed the structural design and testing motion characteristics by using SolidWorks and Simscape toolbox. To enhance the speed performance, it is proposed a High-Speed Proportional Integral Derivative controller (HSPID) based on an improved GA. The comparison response time between uncontrolled and controlled systems proves that the proposed controller produced extreme reduction responses to be measured within the Microsecond unit. Based on trajectory motion, the efficiency of the proposed method is assured by case study motions. The innovative design offers the best solution to rise accurate performance and productivity.

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“…However, the fuzzy law is complex and steady-state error exists in practical application. In addition, some scholars started with the optimization algorithm and combined particle swarm optimization, locust optimization, and an ant lion optimization algorithm with PI control to optimize PI and fuzzy PI parameters, thus improving the control performance [10][11][12][13][14]. Reference [15] combined the back propagation neural network with PI control for automatic parameter adjustment.…”

Section: Introductionmentioning

confidence: 99%

Brain Emotional Learning Control Based on Radial Basis Function for Permanent Magnet Synchronous Motor

Li,

Liang

et al. 2023

Electronics

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It is proposed to use a brain emotional learning control (BELC) system that is based on radial basis function (RBF) in order to enhance the performance of the speed control system of a permanent magnet synchronous motor (PMSM) and its capacity to remain stable following an unexpected load. First, the shortcomings of the traditional PI control in the PMSM speed-control system are explained. The intelligent control system has excellent learning ability and can effectively improve the control effect. The brain emotional learning control is great for nonlinear system control. Thus, it was utilized as the PMSM speed controller in place of the conventional PI control. The RBF neural network was used to optimize some parameters of BELC. Therefore, the process of adjusting parameters in BELC was simplified and the controller ability to resist disturbances was enhanced. The results showed that the brain-based emotional learning control based on RBF optimization (RBF-based BELC) not only improved the speed-control effect of the PMSM system but also enhanced the stability of the torque and current.

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PSO-Based PI Controller for Speed Sensorless Control of PMSM

Cited by 7 publications

References 8 publications

Critical Review on Robust Speed Control Techniques for Permanent Magnet Synchronous Motor (PMSM) Speed Regulation

Critical Review on Robust Speed Control Techniques for Permanent Magnet Synchronous Motor (PMSM) Speed Regulation

Perspective Chapter: Fabulous Design Speed Industrial Robotic Arm

Brain Emotional Learning Control Based on Radial Basis Function for Permanent Magnet Synchronous Motor

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