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.
Bibliographical noteFunding Information:
Manuscript received July 7, 2001; revised March 12, 2002 and May 20, 2002. This work was supported by the Brain Korea 21 Project. W. Chang is with the Samsung Advanced Institute of Technology, Suwon 440-600, Korea (e-mail: changwook@sait.Samsung.co.kr). J. B. Park is with the Department of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, Korea (e-mail: firstname.lastname@example.org). Y. H. Joo is with the School of Electronic and Information Engineering, Kunsan National University, Chonbuk 573-701, Korea (e-mail: email@example.com). Digital Object Identifier 10.1109/TFUZZ.2002.806315
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computational Theory and Mathematics
- Artificial Intelligence
- Applied Mathematics