NDLI: Stochastic stability and performance estimates of packetized unconstrained model predictive control for networked control systems

Content Provider	IEEE Xplore Digital Library
Author	Reble, M. Quevedo, D.E. Allgower, F.
Copyright Year	2011
Description	Author affiliation: Institute for Systems Theory and Automatic Control (IST), University of Stuttgart, Germany (Reble, M.; Allgower, F.) \|\| School of Electrical Engineering & Computer Science, The University of Newcastle, NSW 2308, Australia (Quevedo, D.E.)
Abstract	In this work, we consider the control of discrete-time nonlinear systems over unreliable packet-based communication networks subject to random packet-dropouts. In order to mitigate the influence of the packet dropouts, the controller transmits packets containing control inputs for more than one future time instant. A suitable buffering is then applied at the plant actuator side. Since we do not assume the number of consecutive packet dropouts to be bounded, we are interested in stochastic stability of the closed-loop. For the calculation of the control inputs, we propose an unconstrained model predictive control (MPC) scheme without additional terminal weighting term. This unconstrained MPC scheme shows two significant advantages. First, we do not require the knowledge of a global control Lyapunov function, but instead only a less restrictive controllability assumption, in order to guarantee stochastic stability. Second, guaranteed performance bounds on the expected infinite horizon cost of the closed-loop can be obtained.
Starting Page	171
Ending Page	176
File Size	219650
Page Count	6
File Format	PDF
ISBN	9781457714757
ISSN	19483449
e-ISBN	9781457714764
DOI	10.1109/ICCA.2011.6137929
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-19
Publisher Place	Chile
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Niobium Stability analysis Cost function Numerical stability Stochastic processes Asymptotic stability Lyapunov methods
Content Type	Text
Resource Type	Article

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