A knowledge-based adaptive fuzzy controller for a two-area power system

Abstract

The present paper presents a novel methodology for designing an adaptive fuzzy controller for a dynamically interconnected electric power system. One controller with constant gains for different operating points may not be sufficient to guarantee satisfactory performance for Load frequency control. Therefore, the knowledge-based adaptive fuzzy controller is proposed ether to cope with the operating conditions or to remove any fixed mode. The adaptive fuzzy logic control utilizes the error and the change of error as fuzzy linguistic inputs to regulate the system performance. The proposed control scheme is applied to a two-area power system provided with both hydraulic and thermal turbines.

An Optimal Fuzzy Logic System for a Nonlinear Dynamic System Using a Fuzzy Basis Function

“…We develop an optimal fuzzy logic system, that is, it is optimal in the sense of matching all inputs-outputs pairs in the training set to any given accuracy [15,[17][18][19][20][21]. For an arbitrary Ɛ ˃ 0 , there exists, the difference between a real continuous function g(x) and a fuzzy system F(x) is in the form of :…”

“…The first step in the approximation of such a function is to define the membership function for the input-output spaces, the membership function is expressed by a triangle whose center and width defined by a i and b i respectively [14,15,[17][18][19][20][21] μ x = 1 − 2…”

“…Many types of membership function exists [2,3,[14][15][16][17][18][19][20]. In this paper, the triangular-shaped function µ(e) is the membership function of the error signal, with positive lable"P" and zero Lable "Z" and negative labe "N".…”