Adaptive sliding-mode-observer for sensorless induction motor drive using two-time-scale approach

Mezouar, Abdelkader; Fellah, M.; Hadjeri, Samir

doi:10.1016/j.simpat.2008.06.009

Cited by 33 publications

(20 citation statements)

References 19 publications

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“…The main advantage of the observer to the estimator can be easily shown by equation (15). Indeed, the dynamics of convergence error is controlled by the term (A(Ω)-GC) with the correction gain matrix G.…”

Section: Reduced-order Sliding Mode Speed Observer-based Sensorless Vmentioning

confidence: 99%

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Reduced-Order Sliding Mode Observer-based Speed Sensorless Vector Control of Double Stator Induction Motor

2014

APH

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In this paper a reduced-order sliding mode observer-based speed sensorless vector control of a double stator induction motor (DSIM) is presented. The conventional reduced-order observer has large chattering on the speed and the torque. In order to solve this problem, the sliding mode technique with smooth function is used. The simulation testsshow the effectiveness of the proposed method especially in the load disturbances and/or the change of the reference speed.

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Section: Reduced-order Sliding Mode Speed Observer-based Sensorless Vmentioning

confidence: 99%

“…Many studies have been performed [15][16]. One of them involved replacing the "sign" function by a continuous approximation near the sliding surface.…”

Section: Introductionmentioning

confidence: 99%

Reduced-Order Sliding Mode Observer-based Speed Sensorless Vector Control of Double Stator Induction Motor

2014

APH

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“…The equivalent injection terms [19] can be computed by solving the equation (30) Consequently, (14) and (15) where and . The expressions of the equivalent injection terms and can be deduced from (31) and (32) but these expressions cannot be implemented in practice since and are not available.…”

Section: Assumption (Iii)mentioning

confidence: 99%

“…T HE FACT that the induction motor (IM) is a multivariable, nonlinear and highly coupled process with time-varying parameters, has motivated a lot of work in the control community during the last decade [1]- [14]. The popular alternative method in many drive applications is the field-oriented control (F.O.C.)…”

Section: Introductionmentioning

confidence: 99%

“…Several papers addressed the problem of the online IM parameter estimation [1]- [13], [10], [14]. In [3], [6], [7], [10], [14], the problem of IM time-varying parameter has been studied but experiments have not been carried out to verify the effectiveness of the approaches. In [8], [9], and [13], interesting algorithms for IM parameter estimation are proposed using least square technique but more sophisticated filters are required when PWM inverter is used.…”

Section: Introductionmentioning

confidence: 99%

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An Online Simplified Rotor Resistance Estimator for Induction Motors

Kenné

Simo

Lamnabhi-Lagarrigue

et al. 2010

IEEE Trans. Contr. Syst. Technol.

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Abstract-This brief presents an adaptive variable structure identifier that provides finite time convergent estimate of the induction motor rotor resistance under feasible persistent of excitation condition. The proposed rotor resistance scheme is based on the standard dynamic model of induction motor expressed in a fixed reference frame attached to the stator. The available variables are the rotor speed, the stator currents and voltages. Experiments show that the proposed method achieved very good estimation of the rotor resistance which is subjected to online large variation during operation of the induction motor. Also, the proposed online simplified rotor resistance estimator is robust with respect to the variation of the stator resistance, measurement noise, modeling errors, discretization effects and parameter uncertainties. Important advantages of the proposed algorithm include that it is an online method (the value of can be continuously updated) and it is very simple to implement in real-time (this feature distinguishes the proposed identifier from the known ones).Index Terms-Equivalent injection term, nonlinear observer, online parameter estimation.

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Simulation and hardware implementation of a sensorless modified MPTC for 3φ induction motor drives

Taleshian

Ghanbari

Rakhtala

2021

Int Trans Electr Energ Syst

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Model predictive torque control (MPTC) is developing as a high-performance control system for 3φ induction motor (IM) drives due to its simple structure and fast dynamic response. This paper proposes a sensorless modified MPTC (MMPTC) strategy to control the speed of 3φ IM drives. The suggested scheme uses an improved model reference adaptive system (MRAS) to estimate the rotor speed, motor fluxes, and improvement of the prediction model of the controller. Many experimental and simulation results using DSP/TMS320F28335 controller board and Matlab software are presented to validate the proposed control method. In addition, a comparative study for the traditional sensorless MPTC and proposed MMPTC is experimentally investigated. The presented results show low speed, torque, and flux ripples of the suggested MMPTC system at low-and high-speed ranges.

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Adaptive sliding-mode-observer for sensorless induction motor drive using two-time-scale approach

Cited by 33 publications

References 19 publications

Reduced-Order Sliding Mode Observer-based Speed Sensorless Vector Control of Double Stator Induction Motor

Reduced-Order Sliding Mode Observer-based Speed Sensorless Vector Control of Double Stator Induction Motor

An Online Simplified Rotor Resistance Estimator for Induction Motors

Simulation and hardware implementation of a sensorless modified MPTC for 3φ induction motor drives

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