DocumentCode :
1998798
Title :
Decoupled sliding mode with type 2 fuzzy-neural network controller for multi-machine power systems
Author :
Abbadi, A. ; Hamidia, F. ; Nezli, L. ; Boukhetala, D.
Author_Institution :
Lab. de Rech. en Electrotech. et en Autom., Univ. de Medea, Médéa, Algeria
fYear :
2015
fDate :
25-27 May 2015
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, we propose a decoupled sliding mode with type 2 fuzzy neural network control scheme that has the ability to enhance the transient stability and achieve voltage regulation of on a two-generator infinite bus power system. The design of this controller involves the direct feedback linearization (DFL) technique and the sliding mode (SM) control theory. In this approach, the whole system is decoupled into two subsystems and the state response of each subsystem can be designed to be governed by a corresponding sliding surface. Then a hierarchical sliding mode control approach is designed. The main drawback of SMC is the calculation of equivalent control. To construct the equivalent control law, an adaptive type 2 fuzzy neural network controller is used to approximate the unknown parts of the system. The stability of the closed-loop system is proved mathematically based on the Lyapunov method. Simulation results illustrate the performance of the developed approach regardless of the system operating conditions.
Keywords :
Lyapunov methods; adaptive control; closed loop systems; control system synthesis; feedback; fuzzy control; fuzzy neural nets; hierarchical systems; linearisation techniques; neurocontrollers; power system control; stability; variable structure systems; voltage control; DFL technique; Lyapunov method; adaptive type 2 fuzzy neural network controller; closed-loop system; decoupled sliding mode control; direct feedback linearization; hierarchical sliding mode control design; multimachine power systems; transient stability; two-generator infinite bus power system; voltage regulation; Bismuth; Fuzzy control; Fuzzy neural networks; Generators; Mathematical model; Power system stability; Transient analysis; Adaptive type 2 fuzzy neural network controller; Lyapunov stability; Power system; Sliding mode control; Transient stability; Voltage regulation; type 2Fuzzy logic system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Engineering & Information Technology (CEIT), 2015 3rd International Conference on
Conference_Location :
Tlemcen
Type :
conf
DOI :
10.1109/CEIT.2015.7233055
Filename :
7233055
Link To Document :
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