Daniel Wagner
Czech Technical University in Prague
14 Papers
64 Citations
Daniel Wagner is an academic researcher from Czech Technical University in Prague. The author has contributed to research in topics: Adaptive control & Actuator. The author has an hindex of 5, co-authored 14 publications. Previous affiliations of Daniel Wagner include Missouri University of Science and Technology.
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Papers
Computing actuator bandwidth limits for model reference adaptive control
TL;DR: A linear matrix inequalities-based hedging approach is developed and evaluated for model reference adaptive control of uncertain dynamical systems in the presence of actuator dynamics and proposes a linear matrix inequality-based framework for the computation of the minimum allowable actuator bandwidth limits.
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Computing stability limits for adaptive control laws with high-order actuator dynamics
TL;DR: This paper considers the design of model reference adaptive control laws for uncertain dynamical systems in the presence of high-order actuator dynamics using a linear matrix inequalities-based hedging approach and analyzes the convergence properties of the modified reference model to the ideal reference model.
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An LMI-Based Hedging Approach to Model Reference Adaptive Control With Actuator Dynamics
Benjamin C. Gruenwald,Daniel Wagner,Tansel Yucelen,Jonathan A. Muse +3 more
- 28 Oct 2015
TL;DR: In this paper, a linear matrix inequalities-based hedging approach is developed and evaluated for model reference adaptive control of uncertain dynamical systems in the presence of actuator dynamics, where the hedging method modifies the ideal reference model dynamics in order to allow correct adaptation that does not get affected.
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Model reference adaptive control in the presence of high-order actuator dynamics
Benjamin C. Gruenwald,Tansel Yucelen,Jonathan A. Muse,Daniel Wagner +3 more
- 01 Dec 2016
TL;DR: This paper generalizes a linear matrix inequalities-based hedging approach to high-order (linear time-invariant) actuator dynamics and discusses the distance between the uncertain dynamical system and the ideal (i.e., unmodified) reference model dynamics.
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