Development and Implementation of a Fuzzy-Neural Network Controller for Brushless DC Drives

Gökbulut, Muammer; Dandil, Besir; Bal, Cafer

doi:10.1080/10798587.2007.10642973

Cited by 15 publications

(7 citation statements)

References 21 publications

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“…Hardware in Figure 1, located at the control laboratory of Electronics and Computer Education, University of Firat, has been used for developing advanced control strategies of electrical drives [22]. Now, this article aims at opening the traditional laboratory environment for remote users.…”

Section: Remote Laboratory For Dsp-controlled Induction Motormentioning

confidence: 99%

“…On the other hand, since control system is designed using imperfect and simplified representation of the real system, control algorithm should be checked with the laboratory experiment. DSPs are highly optimized for fast arithmetic [21] and are widely used for developing advanced control strategies in electrical drives [22,23]. Although some remote laboratories using data acquisition cards supported by MWS are proposed [24], very limited DSP-based remote control laboratories for electrical drives are developed.…”

Section: Introductionmentioning

confidence: 99%

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Remote control laboratory for DSP‐controlled induction motor drives

Tekin

Ata

Gökbulut

2012

Comp Applic In Engineering

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ABSTRACT:This article presents an Internet-based remote laboratory for digital signal processor (DSP)-controlled induction motor (IM) drive. The remote experimental rig uses MATLAB/Simulink compatible dSPACE DS1104 signal processor to realize the control algorithm, current control, and PWM modulation. MATLAB RealTime Workshop (RTW) environment provides the real-time operation using a PC and I/O boards and, therefore, application files required for conducting the experiment in laboratory environment can be prepared with the RTW and dSPACE real-time interface (RTI). Also a graphical-user interface can be designed using the dSPACE ControlDesk Developer (CDD). However, for implementation of remote laboratory, interface software between local application and remote users should be developed, since the MATLAB Web Server (MWS) does not allow online access to some hardware such as DS1104 used in this study. For this purpose, an interface using the Python code is developed for remote automation of the ControlDesk. Furthermore, server-client communication software with Delphi programming language is developed for remote implementation of the experiment. Using the user-friendly interface, the Internet-based remote laboratory allows the students to conduct the experiment by changing the predefined control parameters online or uploading the controller designed by the user and then to observe system responses in numerical, graphical, or video format on the remote computer.

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Section: Remote Laboratory For Dsp-controlled Induction Motormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Remote control laboratory for DSP‐controlled induction motor drives

Tekin

Ata

Gökbulut

2012

Comp Applic In Engineering

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“…This technique is complicated for identifying system parameters and is sensitive to fast load variations. Fuzzy logic control (FLC) [5] and neural networks [6] have also been applied to control speed and to achieve high performance and disturbance rejection. However, there is a lack of systematic analysis of FLC stability; also, neurocontroller response to disturbances is slow owing to the learning process.…”

Section: Introductionmentioning

confidence: 99%

Linear-matrix-inequality-based sliding mode control for brushless d.c. motor drives

Soliman

Bayoumi

Soliman

2009

Proceedings of the Institution of Mechanical Engineers, Part I:

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This paper deals with the robust sliding mode control of a brushless d.c. motor drive. A state-space model of the system is developed. The sliding mode controller is separated into linear and non-linear components. The novelty of the approach is in the rationale and method used to synthesize the linear control component which involves a linear matrix inequality (LMI) optimization. System uncertainty due to changes in load inertia is represented as norm bounded. A robust design approach is developed, yielding a robust controller against system uncertainties. A reaching condition to bring the system states to a sliding surface is developed, and the control burden lies heavily on the linear part to alleviate the chattering problem of conventional sliding mode control. The effect of the non-linear component on system performance is analysed. Testing the proposed controller verifies its effectiveness compared with the conventional one.

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“…NFCs have a non-linear structure and does not need the mathematical model of the system to be controlled. Therefore, NFCs are commonly used in nonlinear systems with parameter variation and uncertainty [20][21].…”

Section: Neuro-fuzzy Controller Designmentioning

confidence: 99%

Power Quality Improvement Using Hybrid Passive Filter Configuration for Wind Energy Systems

Keçecioğlu¹,

Açıkgöz²,

Yıldız³

et al. 2017

Journal of Electrical Engineering and Technology

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-Wind energy conversion systems (WECS) which consist of wind turbines with permanent magnet synchronous generator (PMSG) and full-power converters have become widespread in the field of renewable power systems. Generally, conventional diode bridge rectifiers have used to obtain a constant DC bus voltage from output of PMSG based wind generator. In recent years, together advanced power electronics technology, Pulse Width Modulation (PWM) rectifiers have used in WECS. PWM rectifiers are used in many applications thanks to their characteristics such as high power factor and low harmonic distortion. In general, L, LC and LCL-type filter configurations are used in these rectifiers. These filter configurations are not exactly compensate current and voltage harmonics. This study proposes a hybrid passive filter configuration for PWM rectifiers instead of existing filters. The performance of hybrid passive filter was tested via MATLAB/Simulink environment under various operational conditions and was compared with LCL filter structure. In addition, neuro-fuzzy controller (NFC) was preferred to increase the performance of PWM rectifier in DC bus voltage control against disturbances because of its robust and nonlinear structure. The study demonstrates that the hybrid passive filter configuration proposed in this study successfully compensates current and voltage harmonics, and improves total harmonic distortion and true power factor.

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Development and Implementation of a Fuzzy-Neural Network Controller for Brushless DC Drives

Cited by 15 publications

References 21 publications

Remote control laboratory for DSP‐controlled induction motor drives

Remote control laboratory for DSP‐controlled induction motor drives

Linear-matrix-inequality-based sliding mode control for brushless d.c. motor drives

Power Quality Improvement Using Hybrid Passive Filter Configuration for Wind Energy Systems

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