Title
Globally Stabilizing Adaptive Control Design For Nonlinearly-Parameterized Systems
Abstract
In this paper, a new adaptive control design is proposed for nonlinear systems that are possibly non-affine and contain nonlinearly parameterized unknowns. The proposed control is not based on certainty equivalence principle which forms the foundation of existing and standard adaptive control designs. Instead, a biasing vector function is introduced into parameter estimate, it links the system dynamics to estimation error dynamics, and its choice leads to a new Lyapunov-based design so that affine or non-affine systems with nonlinearly parameterized unknowns can be controlled by adaptive estimation. Explicit conditions are found for achieving global asymptotic stability of the state, and the convergence condition for parameter estimation is also found. The conditions are illustrated by several examples and classes of systems. Besides global stability, the proposed adaptive control has the unique feature that it does not contains no robust control part which typically overpowers unknown dynamics, is conservative, and also interferes with parameter estimation.
Publication Date
12-1-2004
Publication Title
Proceedings of the IEEE Conference on Decision and Control
Volume
1
Number of Pages
195-200
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
14344259912 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/14344259912
STARS Citation
Qu, Zhihua; Hull, Richard A.; and Wang, Jing, "Globally Stabilizing Adaptive Control Design For Nonlinearly-Parameterized Systems" (2004). Scopus Export 2000s. 4919.
https://stars.library.ucf.edu/scopus2000/4919