NDLI: A decoupled neuro-sliding mode controller with its application to multimachine power systems

Content Provider	IEEE Xplore Digital Library
Author	Abbadi, A. Nezli, L. Boukhetala, D. Houassine, H.
Copyright Year	2013
Description	Author affiliation: Lab. de Commande des Processus, Ecole Nat. Polytech., El Harrach, Algeria (Nezli, L.; Boukhetala, D.) \|\| Electr. & Comput. Eng. Dept., Univ. of Medea, Medea, Algeria (Abbadi, A.; Houassine, H.)
Abstract	In this paper we propose a decoupled neuro-sliding mode controller that has the ability to enhance the transient stability and achieve voltage regulation simultaneously for multimachine power systems. The design of this controller involves the direct feedback linearization (DFL) technique and the sliding mode control (SMC) 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 drawbacks of SMC are firstly, chattering phenomenon; and secondly the calculation of equivalent control. By introducing the neural network concept to the sliding mode, the chattering is alleviated and the equivalent control is determined with a limited knowledge of the system. Based on only local measurements, the proposed controller is applied to two-generator infinite bus power system. Simulation results illustrate the performance of the developed approach regardless of the system operating conditions.
Sponsorship	IEEE Syst., Man, Cybern. Soc.
Starting Page	23
Ending Page	27
File Size	398916
Page Count	5
File Format	PDF
ISBN	9781467351980
e-ISBN	9781467352000
e-ISBN	9781467351997
DOI	10.1109/ICNSC.2013.6548705
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-10
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power system stability Generators Voltage control Artificial neural networks Transient analysis Mathematical model neural networks Transient stability Voltage regulation Decoupling control
Content Type	Text
Resource Type	Article

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