Field-Oriented Control and Direct Torque Control for Paralleled VSIs Fed PMSM Drives With Variable Switching Frequencies

Wang, Zheng; Chen, Jian; Cheng, Ming; Chau, K. T.

doi:10.1109/tpel.2015.2437893

Cited by 189 publications

(56 citation statements)

References 54 publications

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“…In recent years, the scientific community has paid increasing attention to the chaotic systems and their applications in various areas of science and engineering. Such systems have been investigated in such fields as parameter identifications [14], optimizations [45], electronic circuits [46], electric motor drives [47,48], power electronics [49], communications [50], robotics [51], and many others. Feng et al [52] introduced two means of modifying the inertia weight of a PSO using chaos.…”

Section: Chaos-enhanced Particle Swarm Optimization With Adaptive Parmentioning

confidence: 99%

A Chaos-Enhanced Particle Swarm Optimization with Adaptive Parameters and Its Application in Maximum Power Point Tracking

Hong

Beltran

Paglinawan

2016

Mathematical Problems in Engineering

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This work proposes an enhanced particle swarm optimization scheme that improves upon the performance of the standard particle swarm optimization algorithm. The proposed algorithm is based on chaos search to solve the problems of stagnation, which is the problem of being trapped in a local optimum and with the risk of premature convergence. Type 1 constriction is incorporated to help strengthen the stability and quality of convergence, and adaptive learning coefficients are utilized to intensify the exploitation and exploration search characteristics of the algorithm. Several well known benchmark functions are operated to verify the effectiveness of the proposed method. The test performance of the proposed method is compared with those of other popular population-based algorithms in the literature. Simulation results clearly demonstrate that the proposed method exhibits faster convergence, escapes local minima, and avoids premature convergence and stagnation in a high-dimensional problem space. The validity of the proposed PSO algorithm is demonstrated using a fuzzy logic-based maximum power point tracking control model for a standalone solar photovoltaic system.

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Section: Chaos-enhanced Particle Swarm Optimization With Adaptive Parmentioning

confidence: 99%

A Chaos-Enhanced Particle Swarm Optimization with Adaptive Parameters and Its Application in Maximum Power Point Tracking

Hong

Beltran

Paglinawan

2016

Mathematical Problems in Engineering

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“…An encoder can be connected to the motor or sensorless techniques can be used. Another vector control technique is Direct Torque Control [13]. The torque and stator flux are controlled directly using a switching table which is independent from the current controllers.…”

Section: Introductionmentioning

confidence: 99%

Optimized Field Oriented Control Design by Multi Objective Optimization

Erkol¹

2019

ijacsa

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Permanent Magnet Synchronous Motors are popular electrical machines in industry because they have high efficiency, low ratio of weight/power and smooth torque with no or less ripple. In addition to this, control of synchronous motor is a complex process. Vector control techniques are widely used for control of synchronous motors because they simplify the control of AC machines. In this study, Field Oriented Control technique is used as a speed controller of a Permanent Magnet Synchronous Motor. The controller must be good tuned for applications which need high performance, and classical methods are not enough or need more time to achieve the requested performance criteria. Optimization algorithms are good options for tuning process of controllers. They guarantee finding one of the best solutions and need less time for solving the problem. Therefore, in this study, Tree-Seed Algorithm is used for tuning process of the controller parameters and the results show that Tree-Seed Algorithm is good tool for controller tuning process. The controller is also tuned by Particle Swarm Algorithm to make a comparison. The results show that optimized system by Tree-Seed Algorithm has good performance for the applications which need changing speed and load torque. It has also better performance than the system which is optimized by Particle Swarm Optimization algorithm.

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“…The extension in the market of Permanent Magnet (PM) engine drives has requested the requirement for replication instruments fit for taking care of reenactments for engine drive. Proliferations [2] including engine drives have helped the way toward growing new frameworks by decreasing expense and time. To encourage the improvement of new techniques, recreations of engine drives in a visual situation have the capacities of performing dynamic [3] Simulation.…”

Section: Introduction Amentioning

confidence: 99%

Artificial Neural Networks based SPWM technique for speed control of Permanent Magnet Synchronous Motor

Tummala¹,

Dhasharatha²

2019

E3S Web Conf.

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The advancement of industry apparatuses for some methods with specific tasks to control the working of a few actuators on the field. Among these actuators, Permanent magnet synchronous motor drives are a mainly all-inclusive machine. Proficient utilization of hesitance torque, generally effectiveness, minor misfortunes and smaller size of the motor are the principle attractions of PMSM when contrasted and different drivers. Precise and rapid torque reaction is one of the parameters to determine differentiating arrangements in the ongoing past. The field-situated power perceived the likely and vigorous answer to accomplish these prerequisites to empower the figuring of streams and voltages in different parts of the inverter and motor under transient and consistent conditions. The primary objective of this paper is to investigate Artificial Neural Network based control of speed for PMSM in both open and closed loop under no-load and loaded condition. A shut circle control framework with ANN procedure in the speed circle intended to work in steady torque and transition debilitating districts. MATLAB reproduction performed in the wake of preparing the neural system (directed learning), results for reference control applications are adequate and appropriate in the process business. Speed control in shut circle at different stacking conditions talked about in detail.

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Field-Oriented Control and Direct Torque Control for Paralleled VSIs Fed PMSM Drives With Variable Switching Frequencies

Cited by 189 publications

References 54 publications

A Chaos-Enhanced Particle Swarm Optimization with Adaptive Parameters and Its Application in Maximum Power Point Tracking

A Chaos-Enhanced Particle Swarm Optimization with Adaptive Parameters and Its Application in Maximum Power Point Tracking

Optimized Field Oriented Control Design by Multi Objective Optimization

Artificial Neural Networks based SPWM technique for speed control of Permanent Magnet Synchronous Motor

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