| AUTOMATICALLY EXTRACTING AND OPTIMIZING FUZZY RULE BASE |
| |
| 作者姓名： | Gu Linyue Zhang Liming |
| |
| 作者单位： | Electronic Engineering Department of Fudan University，Shanghai 200433 |
| |
| 基金项目： | Climbing Program-National Key Project for Fundamental research in China, Grant NSC 92097，Shanghai Fundamental Research |
| |
| 摘 要： | A method of automatically extracting and optimizing fuzzy rule base is presented in this paper. Firstly, it applies the method of CCM (cell-to-cell mapping) to analyze the evolving trend and global behavior of a fuzzy dynamical system based on a cell state space, which is characterized by equilibrium, cost and their domain of attractions. Secondly, each rule base is evaluated to determine a performance index based on the information of the system obtained by CCM. Thirdly, CA (Genetic Algorithm) optimizes the coded rule bases according to the performance index generation by generation. The method presented in this paper can be applied to various systems (linear or nonlinear, continuous or discrete) to automatically obtain optimal rule base, for it fuses the advantages of GA and CCM. As an example, a complicated nonlinear system-an inverted pendulum is simulated to demonstrate the validity of the method.
|
Automatically extracting and optimizing fuzzy rule base |
| |
| Gu Linyue Zhang Liming.AUTOMATICALLY EXTRACTING AND OPTIMIZING FUZZY RULE BASE[J].Journal of Electronics,1996,13(4):296-302. |
| |
| Authors: | Gu Linyue Zhang Liming |
| |
| Affiliation: | (1) Electronic Engineering Department of Fudan University, 200433 Shanghai |
| |
| Abstract: | A method of automatically extracting and optimizing fuzzy rule base is presented in this paper. Firstly, it applies the method of CCM (cell-to-cell mapping) to analyze the evolving trend and global behavior of a fuzzy dynamical system based on a cell state space, which is characterized by equilibrium, cost and their domain of attractions. Secondly, each rule base is evaluated to determine a performance index based on the information of the system obtained by CCM. Thirdly, CA (Genetic Algorithm) optimizes the coded rule bases according to the performance index generation by generation. The method presented in this paper can be applied to various systems (linear or nonlinear, continuous or discrete) to automatically obtain optimal rule base, for it fuses the advantages of GA and CCM. As an example, a complicated nonlinear system-an inverted pendulum is simulated to demonstrate the validity of the method. |
| |
| Keywords: | GA( Genetic Algorithm) CCM(Cell-to-Cell Mapping) Chromosome Fit ness Reproduction Crossover Mutation |
| 本文献已被 CNKI SpringerLink 等数据库收录！ |
| 点击此处可从《电子科学学刊(英文版)》浏览原始摘要信息 |
|
点击此处可从《电子科学学刊(英文版)》下载全文 |
