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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
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