Adaptive Neuro-Fuzzy Controller for Synchronous Motor

Aissaoui, Abdel Ghani; Abid, M.; Tahour, Ahmed; Megherbi, Ahmed Chaouki

doi:10.1109/dese.2011.35

Cited by 14 publications

(25 citation statements)

References 6 publications

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“…In this paper, the triangular membership function, the max-min reasoning method, and the center of gravity defuzzification method are used, as those methods are most frequently used in many literatures [20].…”

Section: Fig 6 Basic Structure Of Fuzzy Control Systemmentioning

confidence: 99%

Robust Fuzzy Gains Scheduling of RST Controller for a WECS Based on a Doubly-Fed Induction Generator

et al. 2016

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Original scientific paperThis paper proposes a new robust fuzzy gain scheduling of RST controller for a Wind Energy Conversion System (WECS) based on a doubly fed induction generator (DFIG). First, a designed fuzzy gain scheduling of RST controller is investigated, in which fuzzy rules are utilized on-line to adapt the RST controller parameters based on the error and its first time derivative. The aim of the work is to apply and compare the dynamic performances of two types of controllers (namely, Polynomial RST and Fuzzy-RST) for the WECS. A vector control with stator flux orientation of the DFIG is also presented in order to achieve control of active and reactive power of the wind turbine transmitted to the grid and to make the wind turbine adaptable to different constraints. The results obtained by simulation prove the effectiveness of the proposed controller in terms of decoupling, robustness and dynamic performance for different operating conditions.Key words: Fuzzy gain scheduling, Wind energy conversion system (WECS), Fuzzy-RST, DFIG, Robustness Robusno neizrazito prilagoavanje pojačanja RST regulatora za WECS dvostruko napajani asinkroni generator. U radu je predloženo novo robusno prilagoavanje pojačanja RST regulatora za sustav za pretvorbu energije vjetra (WECS) s dvostruko napajanim asinkronim generatorom (DFIG). Prije svega istražena je sinteza neizrazitog prilagoavanja pojačanja RST regulatora u kojem su neizrazita pravila iskorištena on-line za adaptaciju parametara RST regulatora koji koristi signal pogreške i njegovu prvu vremensku derivaciju. Cilj rada primjena je i usporedba dinamičkih svojstava dva tipa regulatora (polinomski RST i neizraziti RST) za WECS. Takoer je prikazano vektorsko upravljanje s orijentacijom statorskog toka DFIG-a za postizanje upravljanja aktivnom i reaktivnom snagom vjetroagregata koja se predaje mreži te za prilagodbu vjetroagregata za različita ograničenja. Rezultati prikupljeni provedenim simulacijama pokazuju efektivnost predloženog regulatora kroz rasrpegnutost, robusnost i dinamičke performanse za različite uvjete rada.Ključne riječi: Neizrazito prilagoavanje pojačanja regulatora, sustav za pretvorbu energije vjetra (WECS), neizraziti RST, DFIG, robusnost

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Section: Fig 6 Basic Structure Of Fuzzy Control Systemmentioning

confidence: 99%

Robust Fuzzy Gains Scheduling of RST Controller for a WECS Based on a Doubly-Fed Induction Generator

et al. 2016

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“…In fuzzy set terminology, all the possible values that a variable can assume are named universe of discourse, and fuzzy sets (characterized by membership function) cover whole universe of discourse. The shape fuzzy sets can be triangular, trapezoidal, etc [11].…”

Section: Fuzzy Logic Controllermentioning

confidence: 99%

“…The rule base is essentially the control strategy of the system. It is usually obtained from expert knowledge or heuristics; it contains a collection of fuzzy conditional statements expressed as a set of IF-THEN rules, such as: For the given rule base of a control system, the fuzzy controller determines the rule base to be fired for the specific input signal condition and then computes the effective control action (the output fuzzy variable) [11].…”

Section: Fuzzy Logic Controllermentioning

confidence: 99%

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Speed Control of a Doubly Fed Induction Motor using Fuzzy Logic Techniques

Attous¹,

Bekakra²

2010

ijeei

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This paper presents a comparison between a fuzzy logic controller and a conventional IP controller used for speed control with a direct stator flux orientation control of a doubly fed induction motor. The effectiveness of the proposed control strategy is evaluated under different operating conditions such as of reference speed and for load torque step changes at nominal parameters and in the presence of parameter variation. Simulation results show that the fuzzy logic controller is more robust than a conventional IP controller against parameter variation and uncertainty, and is less sensitive to external load torque disturbance with a fast dynamic response. Keywords: direct stator flux orientation control, doubly fed induction motor, fuzzy logic controller, Fuzzy PI controller, conventional IP controller. IntroductionDue to many freedom degrees, the Doubly Fed Induction Machine (DFIM) presents several advantages as well as motor application in high power applications such as traction, marine propulsion or as generator in wind energy conversion systems like wind turbine, or pumped storage systems [1].The DFIM has some distinct advantages compared to the conventional squirrel-cage machine. The DFIM can be fed and controlled stator or rotor by various possible combinations. Indeed, the input-commands are done by means of four precise degrees of control freedom relatively to the squirrel cage induction machine where its control appears quite simpler. The flux orientation strategy can transform the non linear and coupled DFIM-mathematical model to a linear model conducting to one attractive solution as well as under generating or motoring operations [2], [3].Several methods of control are used to control the induction motor among which the vector control or field orientation control that allows a decoupling between the torque and the flux, in order to obtain an independent control of torque and the flux like DC motors [4]. Therefore, decoupling the control scheme is required by compensation of the coupling effect between q-axis and d-axis current dynamics [4].With the field orientation control (FOC) method, induction machine drives are becoming a major candidate in high-performance motion control applications, where servo quality operation is required. Fast transient response is made possible by decoupled torque and flux control. The most widely used control method is perhaps the proportional integral control (PI). It is easy to design and implement, but it has difficulty in dealing with parameter variations, and load disturbances [5]. Recent literature has paid much attention to the potential of fuzzy control in machine drive applications.In the area of the control of the electric machines, the research works are oriented more and more towards the application of the modern control techniques. These techniques involve in a vertiginous way with the evolution of the computers and power electronics. This allows to lead to the industrial processes of high performances. These techniques are the fuzzy control, th...

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“…Thus, the recourse to robust control algorithms is desirable in stabilisation and in tracking trajectories (Mamdani, 1974;Yu et al, 2003;Aissaoui et al, 2011). The control of electrical machines requests best measurement and then sensors with high quality, and then high cost.…”

Section: Introductionmentioning

confidence: 99%

Synchronous motor speed control based on ANFIS methodology and sliding mode observer

Aissaoui

Abid

Tahour

et al. 2015

IJAISC

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Abstract:The application of artificial intelligence has become an important topic in electrical machines control. This paper presents an application of neuro-fuzzy (NF) control for synchronous motor (SM) speed. The NF has the advantages of expert knowledge of the fuzzy inference system and the learning capabilities of neural networks. A neuro-fuzzy controller of the motor speed is then designed and simulated. An asymptotically stable observer is designed to overcome the problem of speed sensor and is obtained without affecting the overall system response. Digital simulation results show that the designed NF speed controller realises a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of load disturbances.

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Adaptive Neuro-Fuzzy Controller for Synchronous Motor

Cited by 14 publications

References 6 publications

Robust Fuzzy Gains Scheduling of RST Controller for a WECS Based on a Doubly-Fed Induction Generator

Robust Fuzzy Gains Scheduling of RST Controller for a WECS Based on a Doubly-Fed Induction Generator

Speed Control of a Doubly Fed Induction Motor using Fuzzy Logic Techniques

Synchronous motor speed control based on ANFIS methodology and sliding mode observer

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