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research article

Reference tracking stochastic model predictive control over unreliable channels and bounded control actions

Mishra, Prabhat K.
•
Diwale, Sanket S.
•
Jones, Colin N.  
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May 1, 2021
Automatica

A stochastic model predictive control framework over unreliable Bernoulli communication channels, in the presence of unbounded process noise and under bounded control inputs, is presented for tracking a reference signal. The data losses in the control channel are compensated by a carefully designed transmission protocol, and those of the sensor channel by a dropout compensator. A class of saturated, disturbance feedback policies is proposed for control in the presence of noisy dropout compensation. A reference governor is employed to generate trackable reference trajectories and stability constraints are employed to ensure mean-square boundedness of the reference tracking error. The overall approach yields a computationally tractable quadratic program, which can be iteratively solved online. (C) 2021 Elsevier Ltd. All rights reserved.

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Type
research article
DOI
10.1016/j.automatica.2021.109512
Web of Science ID

WOS:000634882100016

Author(s)
Mishra, Prabhat K.
Diwale, Sanket S.
Jones, Colin N.  
Chatterjee, Debasish
Date Issued

2021-05-01

Published in
Automatica
Volume

127

Article Number

109512

Subjects

Automation & Control Systems

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Engineering, Electrical & Electronic

•

Automation & Control Systems

•

Engineering

•

tracking

•

stochastic mpc

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bounded controls

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packet dropouts

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networked system

•

output-feedback

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linear-systems

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robust

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stability

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LA3  
Available on Infoscience
April 24, 2021
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/177599
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