𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Tuning fuzzy logic controllers by genetic algorithms

✍ Scribed by F. Herrera; M. Lozano; J.L. Verdegay

Publisher
Elsevier Science
Year
1995
Tongue
English
Weight
692 KB
Volume
12
Category
Article
ISSN
0888-613X

No coin nor oath required. For personal study only.

✦ Synopsis

The performance of a fuzzy logic controller depends on its control rules and membership functions. Hence, it is very important to adjust these parameters to the process to be controlled. A method is presented for tuning fuzzy control rules by genetic algorithms to make the fuzzy logic control systems behave as closely as possible to the operator or expert behavior in a control process. The tuning method fits the membership functions of the fuzzy rules given by the experts with the inference system and the defuzzification strategy selected, obtaining high-performance membership functions by minimizing an error function defined using a set of evaluation input-output data. Experimental results show the method's good performance.

πŸ“œ SIMILAR VOLUMES

A genetic-algorithm-based method for tun
A genetic-algorithm-based method for tuning fuzzy logic controllers
✍ H.B. GΓΌrocak πŸ“‚ Article πŸ“… 1999 πŸ› Elsevier Science 🌐 English βš– 234 KB

It has been demonstrated many times in practice that fuzzy logic controllers have an important role in rule-based expert systems. However, it is essential for a fuzzy logic controller to have an appropriate set of rules to perform at the desired level. The linguistic structure of the fuzzy logic con

Tuning cascade PID controllers using fuz
Tuning cascade PID controllers using fuzzy logic
✍ M.X Li; P.M. Bruijn; H.B. Verbruggen πŸ“‚ Article πŸ“… 1994 πŸ› Elsevier Science 🌐 English βš– 697 KB

## Cascade control configurations offer interesting possibilities to improve the control of processes. However, the tuning of cascade controllers can be quite complex, which hampers a wider spread of applications. Using an on-line pattern recognition approach and fuzzy inferencing it is possible

Tuning fuzzy logic controllers using res
Tuning fuzzy logic controllers using response envelope method
✍ H.B. GΓΌrocak πŸ“‚ Article πŸ“… 2000 πŸ› Elsevier Science 🌐 English βš– 649 KB

A fuzzy logic controller (FLC) is designed based on a human expert's knowledge of the process. The performance of this initial design attempt will, in general, not be satisfactory in terms of certain design criteria such as steady-state error, the oscillatory behavior of the system, etc. This is due

A self-learning and tuning fuzzy logic c
A self-learning and tuning fuzzy logic controller based on genetic algorithms and reinforcements
✍ Hung-Yuan Chung; Chih-Kuan Chiang πŸ“‚ Article πŸ“… 1997 πŸ› John Wiley and Sons 🌐 English βš– 237 KB πŸ‘ 2 views

This article presents a new method for learning and tuning a fuzzy logic controller automatically. A reinforcement learning and a genetic algorithm are used in conjunction with a multilayer neural network model of a fuzzy logic controller, which can automatically generate the fuzzy control rules and