Dynamic Simulations of Adaptive Design Approaches to Control the Speed of an Induction Machine Considering Parameter Uncertainties and External Perturbations

Energies. 2018;11(9):2339 DOI 10.3390/en11092339

 

Journal Homepage

Journal Title: Energies

ISSN: 1996-1073 (Print)

Publisher: MDPI AG

LCC Subject Category: Technology

Country of publisher: Switzerland

Language of fulltext: English

Full-text formats available: PDF, HTML

 

AUTHORS

Kamran Zeb (School of Electrical Engineering, Pusan National University, San 30, ChangJeon 2 Dong, Pusandaehak-ro 63 beon-gil 2, Geumjeong-gu, Busan 46241, Korea)
Waqar U. Din (School of Electrical Engineering, Pusan National University, San 30, ChangJeon 2 Dong, Pusandaehak-ro 63 beon-gil 2, Geumjeong-gu, Busan 46241, Korea)
Muhammad Adil Khan (Department of Electrical and Computer Engineering, Air University Islamabad 44000, Pakistan)
Ayesha Khan (Department of Electrical Engineering University of Management and Technology, Sialkot 51040, Pakistan)
Umair Younas (Department of Electrical Engineering, Selçuk University Konya 42100, Turkey)
Tiago Davi Curi Busarello (Department of Engineering, Federal University of Santa Catarina Blumenau, Rua João Pessoa 2750-89036-256, Brazil)
Hee Je Kim (School of Electrical Engineering, Pusan National University, San 30, ChangJeon 2 Dong, Pusandaehak-ro 63 beon-gil 2, Geumjeong-gu, Busan 46241, Korea)

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 11 weeks

 

Abstract | Full Text

Recently, the Indirect Field Oriented Control (IFOC) scheme for Induction Motors (IM) has gained wide acceptance in high performance applications. The IFOC has remarkable characteristics of decoupling torque and flux along with an easy hardware implementation. However, the detuning limits the performance of drives due to uncertainties of parameters. Conventionally, the use of a Proportional Integral Differential (PID) controller has been very frequent in variable speed drive applications. However, it does not allow for the operation of an IM in a wide range of speeds. In order to tackle these problems, optimal, robust, and adaptive control algorithms are mostly in use. The work presented in this paper is based on new optimal, robust, and adaptive control strategies, including an Adaptive Proportional Integral (PI) controller, sliding mode control, Fuzzy Logic (FL) control based on Steepest Descent (SD), Levenberg-Marquardt (LM) algorithms, and Hybrid Control (HC) or adaptive sliding mode controller to overcome the deficiency of conventional control strategies. The main theme is to design a robust control scheme having faster dynamic response, reliable operation for parameter uncertainties and speed variation, and maximized torque and efficiency of the IM. The test bench of the IM control has three main parts: IM model, Inverter Model, and control structure. The IM is modelled in synchronous frame using d q modelling while the Space Vector Pulse Width Modulation (SVPWM) technique is used for modulation of the inverter. Our proposed controllers are critically analyzed and compared with the PI controller considering different conditions: parameter uncertainties, speed variation, load disturbances, and under electrical faults. In addition, the results validate the effectiveness of the designed controllers and are then related to former works.