DocumentCode :
2330639
Title :
Design and implementation sliding mode controller based on radial basis function neural network for synchronous reluctance motor
Author :
Chen, Chien-An ; Lin, Wen-Bin ; Chiang, Huann-Keng
Author_Institution :
Grad. Sch. of Eng. Sci. & Technolog, Nat. Yunlin Univ. of Sci. & Technol., Douliu
fYear :
2009
fDate :
25-27 May 2009
Firstpage :
281
Lastpage :
286
Abstract :
This paper presents a sliding mode control (SMC) design based on radial basis function neural network (RBFNN) to robust stabilization and disturbance rejection of the synchronous reluctance motor (SynRM) drive system. This method utilizes Lyapunov function and the steep descent rule to guarantee the convergence of the SynRM system asymptotically. Finally, we employ the experiments to validate the proposed method.
Keywords :
Lyapunov methods; control system synthesis; convergence; neurocontrollers; radial basis function networks; reluctance motor drives; robust control; variable structure systems; Lyapunov function; convergence; disturbance rejection; radial basis function neural network; robust stabilization; sliding mode control design; steep descent rule; synchronous reluctance motor drive system; Control systems; Feedforward neural networks; Mathematical model; Neural networks; Radial basis function networks; Reluctance motors; Robust control; Sliding mode control; Synchronous motors; Uncertainty; Lyapunov function; Radial Basis Function Neural Network; Sliding Mode Control; steep descent rule; synchronous reluctance motor;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-2799-4
Electronic_ISBN :
978-1-4244-2800-7
Type :
conf
DOI :
10.1109/ICIEA.2009.5138206
Filename :
5138206
Link To Document :
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