Abstract
In designing a fuzzy model and a fuzzy controller, we encounter a major difficulty in the identification of an optimised fuzzy rule base, which is traditionally achieved by a tedious trial and error process. The paper presents an approach to automatic design of optimal fuzzy rule bases for modelling and control using evolutionary programming. Such programming simultaneously evolves the structure and the parameter of fuzzy rule base for a given task. To check the effectiveness of the suggested approach, five examples for modelling and control are examined. The performance of the identified fuzzy models and fuzzy controllers is demonstrated.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
