Fuzzy logic torque ripple reduction by turn-off angle compensation for switched reluctance motors

Rodrigues, Mickaël; Branco, P. J. Costa; Suemitsu, W.I.

doi:10.1109/41.925598

Cited by 84 publications

(30 citation statements)

References 9 publications

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“…Rodrigues et al [8] implemented fuzzy logic controller for reducing torque ripples through turn off angle. Zhang et al [9] also used fuzzy controller to compute the current compensating signal that added to the main current value in order to reduce torque ripple.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Neuro-fuzzy Controller for Multi-layered Switched Reluctance Motor

Arakat¹,

Haikal²,

Kassem³

2012

IJCA

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There has been big interest in switched reluctance motor (SRM) due to its simplicity and reasonable cost, however excessive torque ripple is one of the major disadvantages of switched reluctance motor. This paper attempts to reduce torque ripples of Switched Reluctance Motor through building multi-layered motor controlled by a hybrid intelligent system known as Adaptive Neuro-fuzzy Inference System ANFIS. Simulation of the proposed motor is conducted using Matlab Simulink environment 2011 and comparison results with single layer switched reluctance motor for both PI and ANFIS controllers show improvement in behavior of MSRM controlled by ANFIS through reduction in speed settling time as well as torque ripples.

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Section: Introductionmentioning

confidence: 99%

Adaptive Neuro-fuzzy Controller for Multi-layered Switched Reluctance Motor

Arakat¹,

Haikal²,

Kassem³

2012

IJCA

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“…However, finding a lumped function for T (u, i j ) is very difficult and demands numerical or experimental data for a specific motor. 14 The aforementioned data have been deduced from the flux linkage curve using equation (5) (see Figure 2).…”

Section: Mathematical Model Of the Systemmentioning

confidence: 99%

Speed robust design of switched reluctance motor for electric vehicle system

Boukhnifer

Chaibet

Ouddah

2017

Advances in Mechanical Engineering

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The strong nonlinear and uncertain parameters of the switched reluctance motor make the traditional controllers difficult to ensure a good performances and stable operation under diverse operating conditions. This work focuses on developing of a new robust design control for switched reluctance motor drives for electrical vehicle to attenuate the effect of disturbances and parameter uncertainties. For this, we have adopted the cascade control architecture (velocity-torque) using two different H ' syntheses (standard and fixed H ' approaches). The first controller of velocity in the outer control loop products the total torque of switched reluctance motor. Hence, a linear equivalent mechanical dynamic is obtained. In the inner control loop, the phase reference current is determined using the torque-angle-current (T À u À i) characteristics stored in lookup table, and the torque is regulated indirectly through the second controller of current. For each control loop, two H ' synthesis approaches are used and compared by m analysis. The simulation and experimental results demonstrate the effectiveness of the designed robust controllers and confirm the ability of the proposed strategies.

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“…"Information and Control" [1965], "Fuzzy sets and systems" [1965], "A fuzzy-set-theoretical interpretation of linguistic hedges" [1972], and related works by others [14]- [16] have been produced to explain the fuzzy logic concept. A fuzzy logic based turn off angle compensator for torque ripple reduction in SRM is proposed [17]. It has been proven that high level of robustness and reliability can be achieved using fuzzy logic based position estimation for sensorless SRMs [18].…”

Section: Introductionmentioning

confidence: 99%

A New Fuzzy Logic based Modeling and Simulation of a Switched Reluctance Motor

Wadnerkar¹,

Bhaskar²,

Das³

et al. 2010

Journal of Electrical Engineering and Technology

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-The switched reluctance motor (SRM) is an older member of the electric machines family. Its simple structure, ruggedness and inexpensive manufacturing potential make it extremely attractive for industrial applications. However, these merits are overshadowed by its inherent high torque ripple, acoustic noise and difficulty to control. In this paper, a control strategy of the angle position control for the SRM drive based on fuzzy logic is illustrated. The input control parameter, the output control parameter and fuzzy control with FAM table formulation strategy are described and simulated with control patterns, and the decision form of the fuzzy control is illustrated and simulated, and the scope of implementing in a Fuzzy based ASIC chip is enlightened with literature support.

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Fuzzy logic torque ripple reduction by turn-off angle compensation for switched reluctance motors

Cited by 84 publications

References 9 publications

Adaptive Neuro-fuzzy Controller for Multi-layered Switched Reluctance Motor

Adaptive Neuro-fuzzy Controller for Multi-layered Switched Reluctance Motor

Speed robust design of switched reluctance motor for electric vehicle system

A New Fuzzy Logic based Modeling and Simulation of a Switched Reluctance Motor

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