Stable multi-input multi-output adaptive fuzzy neural control

Citation
R. Ordonez et Km. Passino, Stable multi-input multi-output adaptive fuzzy neural control, IEEE FUZ SY, 7(3), 1999, pp. 345-353
Citations number
26
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
IEEE TRANSACTIONS ON FUZZY SYSTEMS
ISSN journal
10636706 → ACNP
Volume
7
Issue
3
Year of publication
1999
Pages
345 - 353
Database
ISI
SICI code
1063-6706(199906)7:3<345:SMMAFN>2.0.ZU;2-H
Abstract
In this letter, stable direct and indirect adaptive controllers are present ed that use Takagi-Sugeno (T-S) fuzzy systems, conventional fuzzy systems, or a class of neural networks to provide asymptotic tracking of a reference signal vector for a class of continuous time multi-input multi-output (MIM O) square nonlinear plants with poorly understood dynamics. The direct adap tive scheme allows for the inclusion of a priori knowledge about the contro l input in terms of exact mathematical equations or linguistics, while the indirect adaptive controller permits the explicit use of equations to repre sent portions of the plant dynamics. We prove that with or without such kno wledge the adaptive schemes can "learn" how to control the plant, provide f or bounded internal signals, and achieve asymptotically stable tracking of the reference inputs. We do not impose any initialization conditions on the controllers and guarantee convergence of the tracking error to zero.