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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/71

Title: Anticipatory fuzzy control of power systems
Authors: Dash, P K
Liew, A C
Keywords: Kalman filters
filtering theory
neural nets
fuzzy control
Issue Date: Mar-1995
Publisher: IEE
Citation: IEE Proceedings-Generation, Transmission and Distribution, Vol 142, Iss 2, P 211-218
Abstract: The paper presents an anticipatory fuzzy control scheme to improve the stability of electric power systems. This differs from the traditional fuzzy control in that once the fuzzy-control rules have been used to generate a control value, a predictive routine built into the controller is called for anticipating its effect on the power system output and hence updating the rule base or input-output membership functions in the event of unsatisfactory performance. The effectiveness of the anticipatory and traditional PI fuzzy controllers is demonstrated by simulation studies on a single-machine infinite-bus and multimachine power system subjected to a variety of transient disturbances for different operating conditions. The anticipatory fuzzy control, however, requires a neural network prediction routine using a modified Kalman filter-based fast-learning algorithm
Description: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEE.
URI: http://hdl.handle.net/2080/71
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