A self-organizing fuzzy controller with a fixed maximum number of rules and an ...

• Author(s): Dias, Joana Matos ; Dourado, António
• Date: 1999
• Persistent ID: http://hdl.handle.net/10316/4116
• Origin: Estudo Geral - Universidade de Coimbra
• Subject(s): Empirical research; Control theory; Process control; Self-organizing fuzzy control; On-line learning; Applications
• Document Type: Article
• Language: English

Description

This paper proposes a self-organizing fuzzy controller with a broad generality for minimum phase and stable systems. The controller learns the rules on-line with a minimum knowledge about the process. The rule base is built and permanenetly actualized from input-output real time data and has a fixed maximum number of rules (FMNR). An (on-line) adaptive similarity factor implements a special efficient inference technique. Feedforward and predictive effect is introduced in fuzzification and defuzzification stages. The defuzzification is carried out in such a way that as the learning process progresses the interval of the control becomes more and more accurate. Results are shown concerning simulations for non-linear SISO, MISO and MIMO systems a nd a r eal e xperimental application using a low-cost microcomputer. http://www.sciencedirect.com/science/article/B6V05-3W9M8DR-3/1/ab6da1e2c36b47c90be9ecf551fcd5c2