DocumentCode :
55822
Title :
Fuzzy Virtual Reference Model Sensorless Tracking Control for Linear Induction Motors
Author :
Cheng-Yao Hung ; Liu, Peng ; Kuang-Yow Lian
Author_Institution :
LCD TV Bus. Unit, Wistron Corp., Taipei, Taiwan
Volume :
43
Issue :
3
fYear :
2013
fDate :
Jun-13
Firstpage :
970
Lastpage :
981
Abstract :
This paper introduces a fuzzy virtual reference model (FVRM) synthesis method for linear induction motor (LIM) speed sensorless tracking control. First, we represent the LIM as a Takagi-Sugeno fuzzy model. Second, we estimate the immeasurable mover speed and secondary flux by a fuzzy observer. Third, to convert the speed tracking control into a stabilization problem, we define the internal desired states for state tracking via an FVRM. Finally, by solving a set of linear matrix inequalities (LMIs), we obtain the observer gains and the control gains where exponential convergence is guaranteed. The contributions of the approach in this paper are threefold: 1) simplified approach-speed tracking problem converted into stabilization problem; 2) omit need of actual reference model-FVRM generates internal desired states; and 3) unification of controller and observer design-control objectives are formulated into an LMI problem where powerful numerical toolboxes solve controller and observer gains. Finally, experiments are carried out to verify the theoretical results and show satisfactory performance both in transient response and robustness.
Keywords :
angular velocity control; control system synthesis; convergence of numerical methods; fuzzy control; fuzzy set theory; linear induction motors; linear matrix inequalities; sensorless machine control; stability; FVRM synthesis method; LIM speed sensorless tracking control; LMI problem; Takagi-Sugeno fuzzy model; controller gains; exponential convergence; fuzzy observer gains; fuzzy virtual reference model sensorless tracking control; immeasurable mover speed estimation; linear induction motor speed sensorless tracking control; linear matrix inequalities; numerical toolboxes; secondary flux estimation; state tracking; Force; Fuzzy logic; Induction motors; Mathematical model; Observers; Tracking; Linear induction motors (LIMs); Takagi–Sugeno (TS) fuzzy model; sensorless control; Artificial Intelligence; Computer Simulation; Feedback; Fuzzy Logic; Linear Models; Pattern Recognition, Automated; Transducers;
fLanguage :
English
Journal_Title :
Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
2168-2267
Type :
jour
DOI :
10.1109/TSMCB.2012.2220347
Filename :
6329976
Link To Document :
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