Intelligent Speed Control of Hybrid Stepper Motor Considering Model Uncertainty Using Brain Emotional Learning

Amir Mehdi Yazdani; Amin Mahmoudi; Mohammad Ahmadi Movahed; Pooria Ghanooni; Somaiyeh Mahmoudzadeh; Salinda Buyamin

doi:10.1109/CJECE.2018.2849357

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Intelligent Speed Control of Hybrid Stepper Motor Considering Model Uncertainty Using Brain Emotional Learning

Journal article

Peer reviewed

Intelligent Speed Control of Hybrid Stepper Motor Considering Model Uncertainty Using Brain Emotional Learning

Amir Mehdi Yazdani, Amin Mahmoudi, Mohammad Ahmadi Movahed, Pooria Ghanooni, Somaiyeh Mahmoudzadeh and Salinda Buyamin

Canadian journal of electrical and computer engineering, Vol.41(2), pp.95-104

2018

DOI: https://doi.org/10.1109/CJECE.2018.2849357

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Abstract

Brain emotional learning-based intelligent controller (BELBIC)

hybrid stepper motor (HSM)

speed tracking

uncertainty

This paper presents an implementation of the brain emotional learning-based intelligent controller (BELBIC) for precise speed tracking of the hybrid stepper motor (HSM). Such a configuration is applicable where high resolution and accuracy is essential particularly in uncertain conditions. The proposed controller is a model-free controller independent of the model dynamics and variations that occur in a system. It is capable of autolearning to handle unforeseen disturbances. To evaluate the performance of the BELBIC controller in realistic conditions, the uncertainty of the system as a result of mechanical parameter variation and load torque disturbance is considered. To verify an excellent dynamic performance and the feasibility of the BELBIC, the system is simulated in MATLAB Simulink, and the results of the simulation are compared with an optimized proportional integral (PI) controller. The simulation results confirm the superior performance of the BELBIC for fast and precise speed response as well as its potential in dealing with nonlinearity and uncertainty handling as compared with that of the PI controller. The proposed controller is used in realistic applications, such as tunable-laser system and robot-assisted surgery.

Details

Title: Intelligent Speed Control of Hybrid Stepper Motor Considering Model Uncertainty Using Brain Emotional Learning
Authors/Creators: Amir Mehdi Yazdani - Flinders University
Amin Mahmoudi - Flinders University
Mohammad Ahmadi Movahed - Islamic Azad Univ, Sci & Res Branch, Dept Elect Engn, Tehran 1477893855, Iran
Pooria Ghanooni - Islamic Azad University, Mashhad
Somaiyeh Mahmoudzadeh - Flinders University
Salinda Buyamin - University of Technology Malaysia
Publication Details: Canadian journal of electrical and computer engineering, Vol.41(2), pp.95-104
Publisher: IEEE
Number of pages: 10
Grant note: College of Science and Engineering, Flinders University, Adelaide, SA, Australia
Identifiers: 991005592641907891
Murdoch Affiliation: School of Engineering and Energy; Centre for Water, Energy and Waste
Language: English
Resource Type: Journal article

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Collaboration types: Domestic collaboration; International collaboration
Citation topics: 4 Electrical Engineering, Electronics & Computer Science; 4.18 Power Systems & Electric Vehicles; 4.18.136 Electric Motor Control
Web Of Science research areas: Computer Science, Hardware & Architecture; Engineering, Electrical & Electronic
ESI research areas: Engineering