Acquisition of Fuzzy Control Rules Using Soft Computing Technique

利用软计算技术获取模糊控制规则

• 批准号: 09680385
• 负责人: MIZUMOTO masaharu
• 金额: $ 1.92万
• 依托单位: Osaka Electro-Communication University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 1997
• 资助国家: 日本
• 起止时间: 1997 至 1999
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-09680385/
• 关键词: Fuzzy control rules; Fuzzy singleton-type reasoning method; Fuzzy clustering; Fuzzy functional reasoning method; Tuning; distant-type fuzzy reasoning method; robot with 4 legs; 距離型ファジィ推論; ファジィシングルトン型推論; チューニング; 自律ロボット制御; 関数型推論法; ファジィ規則表

Fuzzy control rules used in fuzzy controls are usually constructed through trial and error by human operators. But it becomes difficult to construct the fuzzy rules by humans when the controlled plants are complicated.This project aims to acquire fuzzy control rules automatically by using soft computing techniques in tuning the antecedent and consequent parts fuzzy rules.New fuzzy reasoning methods for fuzzy controls are proposed such as "fuzzy singleton-type reasoning method", "fuzzy functional reasoning method" and "weighted functional reasoning method", and their relationships are investigated.We give a method of tuning the center and width of the antecedent part as well as the position and weight of the consequent part of fuzzy control rules of fuzzy singleton-type reasoning method by using the deepest decendent method used in the neuro technique and fuzzy clustering method. It is shown from the computer simulation of several functions that this method can generate smaller number of fuzzy control rules compared with the case by the simplified reasoning method which is used usually and widely in fuzzy controls.We propose a distance-type fuzzy reasoning method based on the calculated distance between two fuzzy sets, and discuss robust associative memory algorithm, dynamic reasoning algorithm and unterpolation algorithm in the characteristic space using distant-type fuzzy reasoning method.We consider evolvable hardware using field programmable gate array to run autonomous mobile robot Khepera for collision avoidance. As a new type of chromosome coding in genetic algorithm, tree structure-type chromosome coding is proposed. Moreover, we construct a robot with 4 legs and demonstrate the balance and position controls under fuzzy controls.

在模糊控制中使用的模糊控制规则通常是通过人工操作员的尝试和错误来构造的。但当被控对象较复杂时，人工构造模糊控制规则变得困难，本计画旨在利用软计算技术调整前件及后件模糊规则，以自动获得模糊控制规则，并提出新的模糊控制推理方法，如“模糊单一型推理法”、“模糊函数推理法”及“加权函数推理法”，并研究了它们之间的关系，利用神经技术中的最深下降法和模糊聚类方法，给出了模糊单元型推理方法模糊控制规则前件部分中心和宽度以及后件部分位置和权重的调整方法。多个函数的计算机仿真表明，与模糊控制中常用的简化推理方法相比，该方法可以生成更少数量的模糊控制规则，提出了一种基于计算两个模糊集之间距离的距离型模糊推理方法，并讨论了鲁棒联想记忆算法，动态推理算法和基于距离型模糊推理方法的特征空间内插算法，采用可编程逻辑门阵列的可进化硬件实现了自主移动的机器人Khepera的避碰。提出了一种新的遗传算法染色体编码方式--树结构型染色体编码。此外，我们构建了一个机器人与4条腿，并展示了模糊控制下的平衡和位置控制。

项目成果

Shi, Y. & M. Mizumoto: "A tuning method of fuzzy rules by fuzzy singleton-type reasoning method (Part II)"Proc. of the Fifth International Conference on Soft Computing and Information / Intelligent Systems, Iizuka. 167-170 (1998)

石，Y.

Da Ruan: "Intelligent Hybrid Systems" Kluwev Academic Publisher, 354 (1997)

阮达：《智能混合系统》Kluwev学术出版社，354（1997）

E. Ruspini(分担): "Handbook of Fuzzy Computation"IOP Publishing Ltd.. 785 (1998)

E. Ruspini（合伙人）：《模糊计算手册》IOP Publishing Ltd.. 785 (1998)

M. Mizumoto: "Fuzzy functional reasoning method = weighted functional reasoning method"Proc. of 10th Biomedical Fuzzy Systems Association. 85-88 (1997)

M. Mizumoto：“模糊泛函推理方法=加权泛函推理方法”Proc。

Shi, Y. & M. Mizumoto: "Notes on conventional neuro-fuzzy learning algorithms"Proc. Of the Third Asian Fuzzy Systems Symposium, Masan, Korea. 391-394 (1998)

石，Y.