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Stochastic receding horizon control with output feedback and bounded controls

DSpace at IIT Bombay

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Title Stochastic receding horizon control with output feedback and bounded controls
 
Creator HOKAYEM, P
CINQUEMANI, E
CHATTERJEE, D
RAMPONI, F
LYGEROS, J
 
Subject Predictive control
Output feedback
Constrained control
State estimation
Stochastic control
MODEL-PREDICTIVE CONTROL
ROBUST OPTIMIZATION
STATE
CONSTRAINTS
OPTIMALITY
STABILITY
POLICIES
SYSTEMS
 
Description We study the problem of receding horizon control for stochastic discrete-time systems with bounded control inputs and incomplete state information. Given a suitable choice of causal control policies, we first present a slight extension of the Kalman filter to estimate the state optimally in mean-square sense. We then show how to augment the underlying optimization problem with a negative drift-like constraint, yielding a second-order cone program to be solved periodically online. We prove that the receding horizon implementation of the resulting control policies renders the state of the overall system mean-square bounded under mild assumptions. We also discuss how some quantities required by the finite-horizon optimization problem can be computed off-line, thus reducing the on-line computation. (C) 2011 Elsevier Ltd. All rights reserved.
 
Publisher PERGAMON-ELSEVIER SCIENCE LTD
 
Date 2014-10-16T12:58:09Z
2014-10-16T12:58:09Z
2012
 
Type Article
 
Identifier AUTOMATICA, 48(1)77-88
http://dx.doi.org/10.1016/j.automatica.2011.09.048
http://dspace.library.iitb.ac.in/jspui/handle/100/15606
 
Language en