Stochastic self-triggered model predictive control for linear systems with probabilistic constraints

A stochastic self-triggered model predictive control (SSMPC) algorithm is proposed for linear systems subject to exogenous disturbances and probabilistic constraints. The main idea behind the self-triggered framework is that at each sampling instant, an optimization problem is solved to determine bo...

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Bibliographic Details
Main Authors: Dai, Li, Gao, Yulong, Xie, Lihua, Johansson, Kari Henrik, Xia, Yuanqing
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10356/137852
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Institution: Nanyang Technological University
Language: English