A robust fuzzy speed estimation for vector control of an induction motor

Kouzi, Katia; Said, M-S. Nait; Hilairet, Mickaël; Berthlot, E.

doi:10.1109/ssd.2009.4956814

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…A sliding-mode observer is written in the form, [11]: The sliding mode observer consists of stabilizing the error dynamics of the states to be estimated, which amounts to, [11]:…”

Section: Sliding Mode Observermentioning

confidence: 99%

Online Stator and Rotor Resistance Estimation Scheme Using Sliding Mode Observer for Indirect Vector Controlled Speed Sensorless Induction Motor

Cherifi¹,

Miloud²

2019

AJCST

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Recently, many works have been made to improve the performance of sensorless induction motor drives. However, parameter variations and low-speed operations are the most critical aspects affecting the accuracy and stability of sensorless drives. This work presents a sensorless vector control scheme consisting of the first hand of a velocity estimation algorithm that overcomes the need for sensor velocity and secondly a robust variable structure control law that compensates for the uncertainties present in the system. Simulation results confirm the efficacy of the proposed approach.

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“…A sliding-mode observer is written in the form, [11]: The sliding mode observer consists of stabilizing the error dynamics of the states to be estimated, which amounts to, [11]:…”

Section: Sliding Mode Observermentioning

confidence: 99%

Online Stator and Rotor Resistance Estimation Scheme Using Sliding Mode Observer for Indirect Vector Controlled Speed Sensorless Induction Motor

Cherifi¹,

Miloud²

2019

AJCST

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“…In a reference connected to the stator, we can express the model of the induction machine by the following state equation [1,3]: 11 12 1…”

Section: Induction Motor Modelingmentioning

confidence: 99%

“…Block diagram of the adaptation mechanism of the sliding function ϑ using fuzzy logic When choosing the linguistic value, it should be taken into account that the control must be robust and time of calculation adopted by the fuzzy controller should not be high to not slow down the process [11][12][13]. In this proposed linguistic method we have used 5 rules.…”

Section: Current Observermentioning

confidence: 99%

A New Sliding Mode Speed Observer of Electric Motor Drive Based on Fuzzy-Logic

2014

APH

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In this paper, the speed of the induction machine is controlled by a variable structure controller. To eliminate speed sensor we use a sliding mode observer based on fuzzy logic "FSMSO". The control algorithm and observation is emphasized by simulation tests and it is comapred with the classical sliding mode speed observer"SMSO". Analysis of the results shows the characteristic robustness to disturbances of the load and the speed variation for the FSMSO than SMSO.

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“…The latest generation turbines operate at variable speed. This type of operation has many advantages, such as, operation at maximum power point tracking (MPPT) and higher energy efficiency with low voltage peaks on the components [3]. Compared to fixed speed wind turbines, variable speed wind turbines have the advantage to be supervised by control algorithms, allowing the control of active and reactive powers injected into the grid [4].…”

Section: Introductionmentioning

confidence: 99%

Robust Neural Control of the Dual Star Induction Generator Used in a Grid-Connected Wind Energy Conversion System

Mesai-Ahmed¹,

Bentaallah²,

Cardoso³

et al. 2021

MMEP

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This paper presents a field-oriented control (FOC) of a dual star induction generator (DSIG) applied in a grid-connected wind energy conversion system. Currently, the dual star induction machine (DSIM) is increasingly used among multiphase machines. The machine has two star-connections, sharing the same stator offset, by an electrical angle of 30° and fed by two parallel converters. Maximum power point tracking (MPPT) is illustrated in a first stage, in order to extract a maximum of power under fluctuating wind speed. In a second stage, vector control of a DSIG with FOC is described. Finally, voltage oriented control (VOC) is used to ensure the power factor unity on the grid side. The main contribution of the presented paper is the application of a simple architecture of an artificial neural network (ANN) controller in order to improve the robustness and stability of the system, especially against the parameter change. In comparison with the conventional control, which is known by its sensitivity, the proposed neural MPPT with neural FOC (NMPPT-NFOC) presents better performance under normal and abnormal conditions. The robustness and effectiveness of the proposed control has been validated through illustrative simulation results with different functional zones, and for fixed and variable wind speed.

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A robust fuzzy speed estimation for vector control of an induction motor

Cited by 6 publications

References 13 publications

Online Stator and Rotor Resistance Estimation Scheme Using Sliding Mode Observer for Indirect Vector Controlled Speed Sensorless Induction Motor

Online Stator and Rotor Resistance Estimation Scheme Using Sliding Mode Observer for Indirect Vector Controlled Speed Sensorless Induction Motor

A New Sliding Mode Speed Observer of Electric Motor Drive Based on Fuzzy-Logic

Robust Neural Control of the Dual Star Induction Generator Used in a Grid-Connected Wind Energy Conversion System

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