Speed control of permanent magnet synchronous motor by using fuzzy logic controllers having different inference methods

Aliskan, Ibrahim; Ünsal, Sinan

doi:10.5505/pajes.2016.43788

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…As seen from Figure 1, the electrical expressions in the ABC frame are transformed into 𝛼𝛽 frame with Clarke matrix and then transformed into the d-and q-axes by using Park matrix. (1-3) is obtained when the motor model in ABC frame is transformed into dq-frame based on peak convention (Alışkan and Ünsal, 2018;Koc et al, 2021).…”

Section: Mathematical Modelling Of Ipm Machinesmentioning

confidence: 99%

Investigations of hysteresis based direct torque controlled and field oriented controlled IPM drives for electric vehicle applications

Özçiflikçi

Koç

2022

Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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Direct Torque Control (DTC) techniques are widely used in the control of AC machines as an opponent of space vector pulse width modulation (SVPWM) based field-oriented control (FOC). In the literature, hysteresis-based DTC (HB-DTC) is a vast majority of DTC techniques as the technique do not require a position resolver or an encoder. In this study, HB-DTC and FOC techniques are compared in detail by paying particular attention to current distortions, torque ripple and computational burden. In both techniques, the results have been obtained by simulating a 4.1 kW interior mounted permanent magnet synchronous (IPM) motor which has been designed and manufactured for research and development for electric vehicle traction applications. The results validate that although the HBDTC drives, have pros such as having less computational burden on the processor and eliminating the need for a position sensor, they have relatively much current distortions and torque ripple and hence the results are much deteriorated. Since the modern processors can easily deal with higher computational burden and field-oriented control is feasible in real time, it has been validated by extensive simulations that FOC based IPM drives are superior to their HB-DTC counterparts.

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Section: Mathematical Modelling Of Ipm Machinesmentioning

confidence: 99%

Investigations of hysteresis based direct torque controlled and field oriented controlled IPM drives for electric vehicle applications

Özçiflikçi

Koç

2022

Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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“…The membership grade of the input and output values is calculated by using membership function in Equation (7).…”

Section: Obtained Fuzzrules Of Fuzzy Controllermentioning

confidence: 99%

“…The design of a fuzzy controller is often done by simulation or by performing inputoutput experiments on a prototype of the existing system [4], [5]. As fuzzy controller applications, they used the interactive inverter in the controlled network [6], the speed control of the permanent magnet synchronous motor [7] in their studies of Real Time Control of an Automated Guided Vehicle with Fuzzy Logic [8].…”

Section: Introductionmentioning

confidence: 99%

Optimal Adjustment of Fuzzy Controller Based Evolutionary Algorithms For Driving Electric Motor with Computer Interface

Bulut¹

2020

Preprint

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This study focused on the development of a system based on evolutionary Algorithms to obtain the optimum parameters of the fuzzy controller to increase the convergence speed and accuracy of the controller. The aim of the study is to design fuzzy controller without expert’s knowledge by using evolutionary genetic algorithms and carry out on a DC motor. The design is based on optimization of rule bases of fuzzy controller. In the learning stage, the obtained rule base fitness values are measured by working the rule base on the controller. The learning stage is repeated the termination criteria. The proposed fuzzy controller is performed on the dc motor from a PC program using a interface circuit.

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Optimization of Fuzzy Logic Controller by Using Heuristic Algorithms

Ünsal

Aliskan

2019

J Intell Syst Appl

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There are many design parameters in the structure of fuzzy logic controllers. Conventional methods that don't have a systematic approach are often used in determining of these parameters. However, setting the controller parameters in this way leads to long experiments and this takes a lot of time. For this reason, design parameters of the fuzzy logic controller are usually determined by using heuristic algorithms. Because, heuristic algorithms can offer solutions that are very close to the optimal solution for the problems where exact solution cannot be obtained. In this study, output membership functions of a fuzzy logic controller are optimized using particle swarm optimization and genetic algorithm. Design and optimization stages are explained in detail and results are compared with each other.

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Speed control of permanent magnet synchronous motor by using fuzzy logic controllers having different inference methods

Cited by 3 publications

References 9 publications

Investigations of hysteresis based direct torque controlled and field oriented controlled IPM drives for electric vehicle applications

Investigations of hysteresis based direct torque controlled and field oriented controlled IPM drives for electric vehicle applications

Optimal Adjustment of Fuzzy Controller Based Evolutionary Algorithms For Driving Electric Motor with Computer Interface

Optimization of Fuzzy Logic Controller by Using Heuristic Algorithms

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