Exact linearization of an induction machine with rotoric flux orientation

Bentaallah, Abderrahim; Meroufel, Abdelkader; Bendaoud, Abdelber; Massoum, Ahmed; Fellah, Karim Mohamed

doi:10.2298/sjee0802217b

Cited by 9 publications

(7 citation statements)

References 5 publications

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“…It is desired to control the speed and the norm of the voltage imposes to lower the norm of the flux so one must also control the norm of the rotor flux. In this panel, the outputs must be the rotor speed and the standard (modulus) of the rotor flux [6].…”

Section: B Regulated Outputs and Ordering Criteriamentioning

confidence: 99%

A Fuzzy Adaptive Nonlinear Control for an Asynchronous Machine

Fatima

Assia

Hamdaoui

2019

Carpathian Journal of Electronic and Computer Engineering

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This paper presents the general concept of the nonlinear control of the asynchronous machine. The decoupling between the flux and the speed is realized by the input-output linearization technique. In this work, a nonlinear adaptive control method has been applied to the asynchronous machine and we give some initial results on the adaptive fuzzy logic control of nonlinear systems, linearized by state feedback. The adaptations of the parameters are used as a technique for robustifying the exact cancellation of the nonlinear terms, which is called for the linearization technique. The performance of the proposed nonlinear adaptive control scheme is demonstrated by simulation results. These results show that the proposed method achieves the desired dynamic performance.

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Section: B Regulated Outputs and Ordering Criteriamentioning

confidence: 99%

A Fuzzy Adaptive Nonlinear Control for an Asynchronous Machine

Fatima

Assia

Hamdaoui

2019

Carpathian Journal of Electronic and Computer Engineering

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“…Therefore many studies have been made on motor in order to enhance the performance under these uncertainties such as sliding mode control, predictive control (Orlowska-Kowalska and Dybkowski, 2012;Merabet, 2012;Chen and Dunnigan, 1999;Chiasson, 1996;Marino et al, 1993;Oscar et al, 2012), . and exact feedback linearisation (Bentaallah et al, 2008) to improve the dynamic and response and reduce the complexity of the field oriented control. However these techniques need more sensors to be placed in order to estimate the unmeasured states such as mechanical speed and position where their sensors are more expensive then the machine itself.…”

Section: Introductionmentioning

confidence: 99%

Adaptive nonlinear observer augmented by radial basis neural network for a nonlinear sensorless control of an induction machine

Rabhi¹,

Belkheiri²,

Boufadene³

2018

IJAAC

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This paper presents adaptive neural network nonlinear observer associated with a sensor less nonlinear feedback linearisation controller for induction machine. The proposed observer is used to estimate the mechanical speed using the stator currents measurements and the supplied input voltages; whereas the load torque (unknown disturbance) is estimated using online radial basis neural network function approximation. The stability of the proposed controller-observer is achieved using Lyapunov function. Hence, simulation results have been performed under MATLAB/Simulink shows clearly the performance of the proposed algorithm.

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“…For asynchronous motor feedback exact linearization, especially for high order linearization problem of affine nonlinear systems, less detail theoretical derivation is found in the literature, for instance, the research on static two-phase coordinates of five orders linear affine nonlinear system [8,9]. Under the rotating coordinate system, the reduced order induction motor model with accurate linearization control is discussed [10,11]. But the problem of the stability analysis of an interconnected system that inferred from the theory of EFL controller has not been considered and solved yet.…”

Section: Introductionmentioning

confidence: 99%

Stability Analysis and Design of a Nonlinear Controller for Hot Rolling Coiler

Tong

Yang

2015

Discrete Dynamics in Nature and Society

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For the new style hot rolling coiler which adopt AC asynchronous motor as the driving force and with using the algorithm based on differential geometry design nonlinear controller, precise coiling tension control in the rolling process of strip steel is achieved. In this paper, under the rotating orthogonal coordinate system, the fifth-order nonlinear motor model is selected as the controlled plant. By multi-input multioutput (MIMO) exact feedback linearization (EFL) algorithm, the nonlinear model is transformed to a linear one. In terms of small-gain theorem, it is the first to prove that the nonlinear coiler engine that contains the controller has characteristics of input-to-state stability. Experimental results show that the algorithm can be used for high order tracking control system with time-varying parameters. Even without the traditional flux orientation calculation, the output signals are decoupled. With this controller, the tension deviation is restricted to less than 3% and average rotational speed bias was decreased from 0.5% to 0.1% that ensure high-quality plate cut and surface of strip products.

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Exact linearization of an induction machine with rotoric flux orientation

Cited by 9 publications

References 5 publications

A Fuzzy Adaptive Nonlinear Control for an Asynchronous Machine

A Fuzzy Adaptive Nonlinear Control for an Asynchronous Machine

Adaptive nonlinear observer augmented by radial basis neural network for a nonlinear sensorless control of an induction machine

Stability Analysis and Design of a Nonlinear Controller for Hot Rolling Coiler

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