Direct Adaptive Uncertainty Minimization Framework in the Presence of Unknown Control Effectiveness
Abstract
In recent work, a direct uncertainty minimization framework has been developed and demonstrated for model reference adaptive controllers, which consists of a new architecture involving modification terms in the adaptive controller and the update law. Specifically, these modification terms are constructed through a gradient minimization procedure in order to achieve improved closed-loop system performance with adaptive controllers. In this paper, we generalize this framework for dynamical systems subject to uncertainty in the control effectiveness and provide a detailed stability analysis of the proposed approach. Final version of this paper will also include a detailed application to a hypersonic vehicle model to demonstrate the efflcacy of the proposed framework.
Recommended Citation
B. C. Gruenwald et al., "Direct Adaptive Uncertainty Minimization Framework in the Presence of Unknown Control Effectiveness," 2016 AIAA Guidance, Navigation, and Control Conference, American Institute of Aeronautics and Astronautics, Jan 2016.
Department(s)
Mechanical and Aerospace Engineering
International Standard Book Number (ISBN)
978-162410389-6
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 American Institute of Aeronautics and Astronautics, All rights reserved.
Publication Date
01 Jan 2016