Journal article
Robust precise trajectory tracking of hybrid stepper motor using adaptive critic-based neuro-fuzzy controller
Computers & Electrical Engineering, Vol.81, Art. 106535
2020
Abstract
In this paper, an adaptive critic-based neuro-fuzzy controller (ACNFC) is developed for robust and high-precision speed trajectory tracking of a hybrid stepper motor (HSM). The proposed model-free controller uses the critic-based learning and backpropagation of errors for adaptive tuning of the consequence part of the fuzzy inference rule. This makes the ACNFC reconfigurable and robust in high-precision tracking applications, such as robot-assisted surgery, involving with parametric uncertainties and environmental disturbances. To investigate the performance and robustness of the ACNFC, HSM system is simulated under various conditions in MATLAB/Simulink. These operating conditions consider mechanical parameter variations, load disturbance, noise impact, and sudden fault occurrence. To verify the effectiveness of the proposed controller, test results are compared with the results obtained by optimized-PI and brain emotional learning-based intelligent controllers. Simulation results confirm the effective performance of the ACNFC for adaptive and precise speed response as well as dealing with nonlinearity and uncertainty in realistic applications.
Details
- Title
- Robust precise trajectory tracking of hybrid stepper motor using adaptive critic-based neuro-fuzzy controller
- Authors/Creators
- P. Ghanooni (Author/Creator) - Islamic Azad University, MashhadA.M. Yazdani (Author/Creator) - Murdoch UniversityA. Mahmoudi (Author/Creator) - Flinders UniversityS. MahmoudZadeh (Author/Creator) - Deakin UniversityM. Ahmadi Movahed (Author/Creator)M. Fathi (Author/Creator) - University of Technology Malaysia
- Publication Details
- Computers & Electrical Engineering, Vol.81, Art. 106535
- Publisher
- Elsevier
- Identifiers
- 991005542923407891
- Copyright
- © 2019 Elsevier Ltd
- Murdoch Affiliation
- College of Science, Health, Engineering and Education
- Language
- English
- Resource Type
- Journal article
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InCites Highlights
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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
- Computer Science, Interdisciplinary Applications
- Engineering, Electrical & Electronic
- ESI research areas
- Computer Science