In this paper we extend the classical Lyapunov synthesis method to the domain of computing with words. This new approach is used to design fuzzy controllers. Assuming minimal knowledge about the plant to be controlled, the proposed method enables us to systematically derive the fuzzy rules that cons
โฆ LIBER โฆ
Neural and fuzzy approaches to vision-based parking control
โ Scribed by W.A. Daxwanger; G. Schmidt
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 685 KB
- Volume
- 4
- Category
- Article
- ISSN
- 0967-0661
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Fuzzy Lyapunov-based approach to the des
โ
Michael Margaliot; Gideon Langholz
๐
Article
๐
1999
๐
Elsevier Science
๐
English
โ 593 KB
Fuzzy neural-based approaches for effici
โ
Said Gaoua; Limin Ji; Ze Cheng; Farah A. Mohammadi; Mustapha C. E. Yagoub
๐
Article
๐
2009
๐
John Wiley and Sons
๐
English
โ 327 KB
Fuzzy knowledge-based approach to treati
โ
Dobrila Petrovic; Edward Sweeney
๐
Article
๐
1994
๐
Elsevier Science
๐
English
โ 513 KB
Development of emission orientated produ
โ
Axel Tuma; Hans-Dietrich Haasis; Otto Rentz
๐
Article
๐
1996
๐
Elsevier Science
๐
English
โ 582 KB
A knowledge-based approach to improve ne
โ
Mo-Yuen Chow; Jason T. Teeter
๐
Article
๐
1995
๐
Elsevier Science
๐
English
โ 745 KB
A fuzzy neural network and its applicati
โ
Sun Zengqi; Deng Zhidong
๐
Article
๐
1996
๐
Elsevier Science
๐
English
โ 503 KB
A fuzzy neural network is presented. The network is composed of two parts: an antecedent network and a consequent network. The network acts as a fuzzy logic controller. The antecedent network matches the premises of the fuzzy rules and the consequent network implements the consequences of the rules.