Title :
Complex system inference-control and fuzzy logic modeling
Author :
Dou, Charlie ; Macedo, J.A.
Author_Institution :
Dept. of Math. Phys. Sci. & Eng. Technol., West Texas A&M Univ., TX, USA
Abstract :
This report systematically reviews the historical development, theoretical research and practical application of the fuzzy logic inference-control modeling (FLM) for the complex systems-multiple-input-multiple-output (MIMO) systems and nonlinear systems. The most common and important issues related with fuzzy models: self-organizing FLM, adaptive FLM, general purpose FLM, Mamdani-FLM and Tagagi-Sugeno-Kang FLM, fuzzy vector-spaces, hierarchical structured FLM, and fuzzy phase-plane, are exhibited, analyzed, or compared. The survey reveals that the design of inference and control system, especially for MIMO systems and nonlinear systems with uncertainty, can be considered through multiple scenarios, not just their rigid dynamic mathematical models but also fuzzy logic models
Keywords :
MIMO systems; fuzzy control; inference mechanisms; large-scale systems; MIMO systems; complex system inference-control; fuzzy logic inference-control modeling; fuzzy logic modeling; fuzzy phase-plane; multiple scenarios; multiple-input-multiple-output systems; nonlinear systems; rigid dynamic mathematical models; Control system synthesis; Control theory; Fuzzy logic; Fuzzy set theory; Integrated circuit modeling; MIMO; Mathematical model; Mathematics; Nonlinear systems; Programmable control;
Conference_Titel :
Uncertainty Modeling and Analysis, 1995, and Annual Conference of the North American Fuzzy Information Processing Society. Proceedings of ISUMA - NAFIPS '95., Third International Symposium on
Conference_Location :
College Park, MD
Print_ISBN :
0-8186-7126-2
DOI :
10.1109/ISUMA.1995.527724
