## 摘要

This paper proposes a systematic method to design a multivariable fuzzy logic controller (SMFLC) for large-scale nonlinear systems. In designing a fuzzy logic controller, the major task is to determine fuzzy rule bases, membership functions of input/output variables, and input/output scaling factors. In this work, the fuzzy rule base is generated by a rule-generated function, which is based on the negative gradient of a system performance index, the membership functions of isosceles triangle of input/output variables are fixed in the same cardinality and only the input/output scaling factors are generated from a genetic algorithm based on a fitness function. As a result, the searching space of parameters is narrowed down to a small space, the multivariable fuzzy logic controller can quickly constructed, and the fuzzy rules and the scaling factors can easily be determined. The performance of the proposed method is examined by computer simulations on a Puma 560 system and a two-inverted pendulum system.

原文 | 英語 |
---|---|

頁（從 - 到） | 741-752 |

頁數 | 12 |

期刊 | IEEE Transactions on Fuzzy Systems |

卷 | 7 |

發行號 | 6 |

DOIs | |

出版狀態 | 已發佈 - 1999 12月 |

對外發佈 | 是 |

## ASJC Scopus subject areas

- 控制與系統工程
- 計算機理論與數學
- 人工智慧
- 應用數學