Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
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In this paper, a new fuzzy controller is proposed based on inverse model of boiler-turbine system. Gain scheduling scheme is used to keep feedback rule as close as possible to optimal condition while generating plant Input/Output data. Interaction between state variables of the system is studied and as a result, a MIMO structure controller is developed. Considering possible operating zone, number of rules in Sugeno-type FIS is reduced. It is shown that the proposed controller has better performance such as smaller rise time than the optimal controller. It is also shown that the controller has robust performance in the presence of uncertainty and parameters variation.