GA-based intelligent digital redesign of fuzzy-model-based controllers

Abstract

Intelligent digital redesign involves converting a continuous-time fuzzy-model-based controller into an equivalent discrete-time counterpart for the digital control of continuous-time nonlinear systems by using the Takagi-Sugeno (TS) fuzzy models. In this paper, authors present a new global state-matching intelligent digital redesign method for nonlinear systems by using genetic algorithms (GAs). More precisely, the intelligent digital redesign problem is converted to an equivalent optimization problem, and then GAs are adopted to find a solution. The search space, in which each problem variable is defined for GAs, are systematically obtained by the interval arithmetic operations. The proposed method results in global matching of the states of the analogously controlled system with those of the digitally controlled system while the conventional intelligent digital redesign method does not. The Chen's chaotic system is used as an illustrative example to show the effectiveness and the feasibility of the developed method. The proposed method provides a new approach for the digital redesign of a class of fuzzy-model-based controllers.

Genetic Algorithm Based Fuzzy Logic Controller for Wire-EDM Machine

“…Recent works have shown that GAs have the properties that make them a powerful technique for selecting high-performance parameters for FLCs. A simple schematic illustration of the process of GA is shown in work [1]. As shown in Fig.…”

“…Wire electrical discharge machining (wire-EDM) has become a key technology for the manufacture of stamping, pressing and extrusions tools [1]. A closed-loop wire tension control system with an adaptive controller for a wire-EDM machine has been shown to keep a constant tension value as well as successfully improve the machining accuracy [2][3].…”