Adaptive fuzzy variable structure control of induction motors

Agamy, Mohammed; Yousef, Hassan; Sebakhy, O.A.

doi:10.1109/ccece.2004.1344964

Cited by 14 publications

(9 citation statements)

References 20 publications

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“…It is also assumed that this bound is unknown, therefore we use an estimation of E , which is denoted by Ê . Consequently, from (14) and (22) we have…”

Section: The Proposed Control Lawmentioning

confidence: 99%

Position control of induction and DC servomotors: a novel adaptive fuzzy PI sliding mode control

Shahnazi

Shanechi

Pariz

2006

2006 IEEE Power Engineering Society General Meeting

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The position control of a class of servomotors is addressed in this paper via a novel adaptive fuzzy PI sliding mode control. The premise and the consequence parts of the fuzzy rules are tuned with adaptive schemes. To attenuate chattering effectively the discontinuous control is approximated by an adaptive PI control structure. Moreover, the bound of the discontinuous control term is assumed unknown and an adaptive mechanism is used to estimate this bound. All adaptive laws are derived via Lyapunov synthesis method, thereby guaranteeing the closed-loop stability. The proposed approach has the added advantage that for external disturbances it only requires a bound to exist, without needing to know the magnitude of this bound. The proposed controller is applied to control a model of uncertain induction servomotor subject to significant disturbances and a model of DC servomotor with unknown parameters and uncertainty in load condition. Analysis of simulations reveals the effectiveness of the proposed method in controlling servomotors in terms of significant reduction in chattering while maintaining asymptotic convergence.

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“…It is also assumed that this bound is unknown, therefore we use an estimation of E , which is denoted by Ê . Consequently, from (14) and (22) we have…”

Section: The Proposed Control Lawmentioning

confidence: 99%

Position control of induction and DC servomotors: a novel adaptive fuzzy PI sliding mode control

Shahnazi

Shanechi

Pariz

2006

2006 IEEE Power Engineering Society General Meeting

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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%

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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Adaptive fuzzy variable structure control of induction motors

Cited by 14 publications

References 20 publications

Position control of induction and DC servomotors: a novel adaptive fuzzy PI sliding mode control

Position control of induction and DC servomotors: a novel adaptive fuzzy PI sliding mode control

Adaptive fuzzy vector control for a doubly-fed induction motor

Fuzzy Adaptive Controller for a DFI-Motor

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