Adaptive model predictive control for actuation dynamics compensation in real-time hybrid simulation
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Author / Producer
Date
2022-06
Publication Type
Journal Article
ETH Bibliography
yes
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Abstract
Hybrid simulation is used to obtain the dynamic response of a system whose components consist of physical and numerical substructures. The coupling of these substructures is achieved by actuation systems, which are commanded in closed-loop control setting. To ensure high fidelity of such hybrid simulations, performing them in real-time is necessary. However, real-time hybrid simulation poses challenges since the inherent dynamics of the actuation system introduce time delays, thus modifying the dynamic response of the investigated system. Therefore, a tracking controller is required to adequately compensate for such time delays. In this study, a novel tracking controller is proposed for dynamics compensation in real-time hybrid simulations. It is based on adaptive model predictive control, a linear time-varying Kalman filter, and a real-time model identification algorithm. Within the latter, auto-regressive exogenous polynomial models are identified in real-time to estimate the changing plant dynamics. A parametric virtual case study, encompassing a virtual motorcycle, is used to validate the performance and robustness of the proposed controller. Results demonstrate the effectiveness of the proposed controller for real-time hybrid simulations.
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Publication status
published
Editor
Book title
Journal / series
Volume
172
Pages / Article No.
104817
Publisher
Elsevier
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Real-time hybrid simulation; Adaptive model predictive control; Kalman filter; Real-time model identification; Dynamic response; Actuation dynamics compensation
Organisational unit
02605 - Institut für Baustatik u. Konstruktion / Institute of Structural Engineering