Paper Info
Title
An adaptive supervisory sliding fuzzy cerebellar model articulation controller for sensorless vector-controlled induction motor drive systems.
Abstract
This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes-the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC-were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.
Year
DOI
Venue
2015
10.3390/s150407323
SENSORS
Keywords
Field
DocType
biomedical research,bioinformatics
Convergence (routing),Intelligent control,Vector control,Induction motor,Control theory,Performance index,Control theory,Mean squared error,Control engineering,Engineering,Fuzzy cerebellar model articulation controller
Journal
Volume
Issue
ISSN
15
4
1424-8220
Citations 
PageRank 
References 
2
0.41
4
Authors
5
Name
Order
Citations
PageRank
Shun-Yuan Wang120.41
Chwan-Lu Tseng220.41
Shou-Chuang Lin320.41
Chun-Jung Chiu420.41
Jen-Hsiang Chou564.40