Unconstrained tracking MPC for continuous-time nonlinear systems

In this paper, we extend unconstrained model predictive control (MPC) from setpoint stabilization to dynamic reference tracking for continuous-time nonlinear systems. In particular, we focus on the case when the reference cannot be perfectly tracked by the system due to dynamics and/or constraints....

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Main Authors: Long, Yushen, Xie, Lihua
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/159357
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1593572022-06-16T02:59:23Z Unconstrained tracking MPC for continuous-time nonlinear systems Long, Yushen Xie, Lihua School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Model Predictive Control Tracking Control In this paper, we extend unconstrained model predictive control (MPC) from setpoint stabilization to dynamic reference tracking for continuous-time nonlinear systems. In particular, we focus on the case when the reference cannot be perfectly tracked by the system due to dynamics and/or constraints. Under the incremental stabilizability assumption and an additional dissipativity assumption, the practical stability of tracking the unknown optimal reachable reference trajectory is proved even though the controller does not know such a reference explicitly. Agency for Science, Technology and Research (A*STAR) National Research Foundation (NRF) The work of Long and Xie is funded by the Republic of Singapore’s National Research Foundation through a grant to the Berkeley Education Alliance for Research in Singapore (BEARS) for the Singapore Berkeley Building Efficiency and Sustainability in the Tropics (SinBerBEST) Program. BEARS has been established by the University of California, Berkeley as a center for intellectual excellence in research and education in Singapore. The work of Long is also funded by A*ccelerate Gap-funded Project No. ACCL200013. 2022-06-16T02:59:23Z 2022-06-16T02:59:23Z 2021 Journal Article Long, Y. & Xie, L. (2021). Unconstrained tracking MPC for continuous-time nonlinear systems. Automatica, 129, 109680-. https://dx.doi.org/10.1016/j.automatica.2021.109680 0005-1098 https://hdl.handle.net/10356/159357 10.1016/j.automatica.2021.109680 2-s2.0-85107131327 129 109680 en ACCL200013 Automatica © 2021 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Model Predictive Control
Tracking Control
spellingShingle Engineering::Electrical and electronic engineering
Model Predictive Control
Tracking Control
Long, Yushen
Xie, Lihua
Unconstrained tracking MPC for continuous-time nonlinear systems
description In this paper, we extend unconstrained model predictive control (MPC) from setpoint stabilization to dynamic reference tracking for continuous-time nonlinear systems. In particular, we focus on the case when the reference cannot be perfectly tracked by the system due to dynamics and/or constraints. Under the incremental stabilizability assumption and an additional dissipativity assumption, the practical stability of tracking the unknown optimal reachable reference trajectory is proved even though the controller does not know such a reference explicitly.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Long, Yushen
Xie, Lihua
format Article
author Long, Yushen
Xie, Lihua
author_sort Long, Yushen
title Unconstrained tracking MPC for continuous-time nonlinear systems
title_short Unconstrained tracking MPC for continuous-time nonlinear systems
title_full Unconstrained tracking MPC for continuous-time nonlinear systems
title_fullStr Unconstrained tracking MPC for continuous-time nonlinear systems
title_full_unstemmed Unconstrained tracking MPC for continuous-time nonlinear systems
title_sort unconstrained tracking mpc for continuous-time nonlinear systems
publishDate 2022
url https://hdl.handle.net/10356/159357
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