Adaptive fuzzy mimo control of induction motors

Yousef, Hassan; Wahba, Manal A.

doi:10.1016/j.eswa.2008.04.004

Cited by 29 publications

(23 citation statements)

References 6 publications

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“…Motivated by the above works [5][6][7][8][9][11][12][13][14][15], in this paper, we design an adaptive fuzzy vector control system for a DFIM with uncertain dynamics. The control design is carried out using an appropriate backstepping procedure bearing in mind the asymptotic stability of the overall control system.…”

Section: Introductionmentioning

confidence: 99%

“…The simulation results for different situations show the performance of this controller in the presence of varying operating conditions, dynamical uncertainties, and external load disturbance. Some adaptive fuzzy controllers for induction motors (IM) have been developed in [13][14][15] using the ability of fuzzy systems for approximating of the nonlinear uncertain functions. The stability of the closed loop system is proven by a Lyapunov approach.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive fuzzy vector control for a doubly-fed induction motor

et al. 2015

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy vector control for a doubly-fed induction motor

et al. 2015

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“…Then, it is necessary to add some form of adaptation that updates the controller parameters in order to maintain and improve the control performance in wide range of changing conditions Lee (1990); Li and Lau (1989). Using fuzzy systems for approximating of the nonlinear uncertain functions, adaptive fuzzy controllers for inductions motors (IM) have been developed in Agamy et al (2004), Lin et al (2002), Youcef and Wahba (2009). Therefore, the motivation of this chapter is the design of a nonlinear controller for DFI-Motor drives which guarantees speed tracking and reactive power regulation at stator side.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Adaptive Controller for a DFI-Motor

Bounar

Boulkroune

Boudjema

2014

Complex System Modelling and Control Through Intelligent Soft Computations

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This chapter mainly deals with the fuzzy adaptive backstepping control (FABC) design of a doubly-fed induction motor (DFI-Motor). The proposed controller guarantees speed tracking and reactive power regulation at stator side. The DFI-Motor is controlled by acting on the rotor winding and its stator is directly connected to the grid. In the controller designing, a state-all-flux DFI-Motor model with stator voltage vector oriented reference frame is exploited. Our approach is based on the decomposition of the motor model in two coupled subsystems; the stator flux and the speed-rotor flux subsystems. Under some considerations on the system model, the DFI-Motor unity power factor control and speed tracking problem is transferred to the rotor flux control problem. In our control approach, the unknown load torque is estimated on-line by a suitable adaptive law and the nonlinear functions appearing in the tracking errors dynamics and uncertainties are reasonably approximated by adaptive fuzzy systems. A rigorous stability analysis based on Lyapunov theory is performed to guarantee that the complete control system is asymptotically stable. Furthermore, numerical simulation results are provided to verify the effectiveness of the proposed FABC approach.

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“…In the last two decades, many studies have been developed around fuzzy law control [4], [5], [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Takagi-Sugeno fuzzy control of a synchronous machine

Ouaaline

Elalami

2010

2010 Conference on Control and Fault-Tolerant Systems (SysTol)

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This paper describes the results of an application of a PDC type T-S fuzzy control to synchronous machine. The non linear mathematical model for the proposed synchronous machine adopted in this work is described by T-S continuous fuzzy models. Next, the control law for T-S fuzzy control based on PDC design is studied. The stability and the stabilisation of the whole closed-loop model are investigated using the quadratic lyaponov function. These conditions were reformulated into terms of Linear Matrix Inequalities (LMI) problem by using a Schur complement. Simulation results for synchronous machine demonstrate the PDC controller's effectiveness.

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Adaptive fuzzy mimo control of induction motors

Cited by 29 publications

References 6 publications

Adaptive fuzzy vector control for a doubly-fed induction motor

Adaptive fuzzy vector control for a doubly-fed induction motor

Fuzzy Adaptive Controller for a DFI-Motor

Takagi-Sugeno fuzzy control of a synchronous machine

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