Hybrid intelligent controller based torque ripple minimization in switched reluctance motor drive

Pushparajesh, V.; Nandish, B M; Marulasiddappa, H. B.

doi:10.11591/eei.v10i3.3039

Cited by 10 publications

(10 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We call the former "flux acceleration" and the latter "flux deceleration," respectively, when the value is positive or negative. Therefore, the following constitutes a definition of a novel approach to SRM regulation [11].…”

Section: Control Strategymentioning

confidence: 99%

Classical Direct Torque Control for Switched Reluctance Motor Drive

Pushparajesh¹,

Nandish²

2023

New Trends in Electric Machines - Technology and Applications

Self Cite

View full text Add to dashboard Cite

The modern electrical machines require higher efficiency in concern with pollution of the environment. Industries are focusing on bringing out new avenues in controlling the electric motors to adjust the speed and torque without compromising. The Direct Torque Control technique is suggested in this study. Slip control, which exploits a peculiar link between slip and torque, is the basic concept underlying this regulation. Direct torque control provides various benefits over field-oriented control, including reduced sensitivity to machine parameters, easy assembly, and quick dynamic torque response. As the voltage space vector is chosen in response to the inaccuracy in the flux linkage and torque, a current controller is unnecessary in this design. Low torque ripple, reduced noise, and reduced mechanical vibration are all attainable through proper torque management in the switching reluctance motor.

show abstract

Section: Control Strategymentioning

confidence: 99%

Classical Direct Torque Control for Switched Reluctance Motor Drive

Pushparajesh¹,

Nandish²

2023

New Trends in Electric Machines - Technology and Applications

Self Cite

View full text Add to dashboard Cite

show abstract

“…The results indicate the better performance of the ANFIS controller compared to two other methods. In [30], an intelligent genetic neural network controller is proposed for minimizing a synchronous reluctance motor torque ripple. Simulation results show that, by using the proposed hybrid controller, the torque ripples vary between 3.25% and 1.7%.…”

Section: A Review Of the Research Backgroundmentioning

confidence: 99%

“…In any case, the initial values for α and β in O and A, and functions R and S for generating emotional signals, must be selected. Here, the functions g and f are defined according to Equation (30) and can be defined according to the control need of the user:…”

Section: Model Of Emotional Controllermentioning

confidence: 99%

Performance Improvement of Reluctance Synchronous Motor Using Brain Emotional Learning Based Intelligent Controller

et al. 2021

View full text Add to dashboard Cite

In this paper, intelligent control of a reluctance synchronous motor by an emotional controller, considering the effect of magnetic saturation on implementation, is analyzed; the maximum torque per ampere (MTPA) strategy is provided. According to the application of the proposed control scheme, the structure adequately performs the control of speed and magnetic flux of the reluctance synchronous motor drive. Additionally, the application of intelligent control based on an emotional learning system has provided adequate results to create a proper control process. The control function of a SynRM drive based on vector control in a rotor machine was compared with another based on emotional controllers and a PI controller regulated by genetic algorithms. The result of this comparison was the improvement of control functions by the controller based on the emotional controller. In addition, the MTPA based on search algorithms was well implemented in different situations. Due to its simplicity and independence from system parameters, the emotional controller can be considered as a potential operational method in the industry.

show abstract

“…Applying this control technique to reduce torque ripple in an SRM is not allowed because to the chattering issue. Furthermore, Pushparajesh et al [24] propose a direct torque scheme based on genetic neural network controllers to decrease the switched reluctance motor torque ripple. A drawback of that method is when compared to the set performance, the calculation time is a little higher.…”

Section: Introductionmentioning

confidence: 99%

Accounting for magnetic saturation in designing a SRM speed controller for torque ripple minimization

Boumaalif

Ouadi

2023

IJPEDS

View full text Add to dashboard Cite

This study established a nonlinear control design for switched reluctance motor (SRM) vehicle applications, using the backstepping approach. The suggested controller is established according to a model that consider magnetic saturation while reducing torque ripple and resulting in less vibrations. To optimize torque ripple, control angles are adjusted based on the machine speed and torque measurements. Indeed, a lookup table is constructed, offering the efficient control angles for various motor operating points. The suggested control technique was validated through simulation, exploiting an accurate MATLAB SRM model considering magnetic saturation effects. To illustrate the superiority of the suggested regulator, a comparison of its performance with a proportional-integral (PI) controller was performed. The acquired findings indicate the suggested regulator’s effectiveness.

show abstract

Hybrid intelligent controller based torque ripple minimization in switched reluctance motor drive

Cited by 10 publications

References 28 publications

Classical Direct Torque Control for Switched Reluctance Motor Drive

Classical Direct Torque Control for Switched Reluctance Motor Drive

Performance Improvement of Reluctance Synchronous Motor Using Brain Emotional Learning Based Intelligent Controller

Accounting for magnetic saturation in designing a SRM speed controller for torque ripple minimization

Contact Info

Product

Resources

About