Abstract
A challenging problem for adaptive control systems is the accurate characterization of the transient response in the presence of dynamic uncertainties such as a partially known actuator. Considering an actuator modelled as a first order filter with an uncertain control effectiveness and using a projection mechanism for parameters adaptation, we show that the tracking error dynamics behaves as a linear system perturbed by bounded uncertainties. This brings the advantage that the stability analysis can be cast in terms of LMIs so that convex optimization tools can be used for analysis and design. In this framework we propose a mixed linear/adaptive control strategy whose parameters are computed via a convex Mult objective optimization in order to ensure, at the same time, the evolution of the error within a minimal size invariant set, while the added linear gain is minimized. A Numerical example is provided to demonstrate the efficacy of the method.
Recommended Citation
M. L. Fravolini et al., "Analysis and Design of Adaptive Control Systems with Unmodeled Input Dynamics Via Multiobjective Convex Optimization," Proceedings of the American Control Conference, pp. 1579 - 1584, article no. 7170958, Institute of Electrical and Electronics Engineers, Jul 2015.
The definitive version is available at https://doi.org/10.1109/ACC.2015.7170958
Department(s)
Mechanical and Aerospace Engineering
International Standard Book Number (ISBN)
978-147998684-2
International Standard Serial Number (ISSN)
0743-1619
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
28 Jul 2015
