Bernardini, Daniele and Donkers, M.C.F. and Bemporad, Alberto and Heemels, W.P.M.H. A model predictive control approach for stochastic networked control systems. In: 2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems. IFAC. ISBN 978-3-902661-82-1 (2010)Full text not available from this repository.
In this paper we present a stochastic model predictive control (SMPC) approach for networked control systems (NCSs) that are subject to time-varying sampling intervals and time-varying transmission delays. These network-induced uncertain parameters are assumed to be described by random processes, having a bounded support and an arbitrary continuous probability density function. Assuming that the controlled plant can be modeled as a linear system, we present a SMPC formulation based on scenario enumeration and quadratic programming that optimizes a stochastic performance index and provides closed-loop stability in the mean-square sense. Simulation results are shown to demonstrate the performance of the proposed approach.
|Item Type:||Book Section|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TJ Mechanical engineering and machinery
|Research Area:||Computer Science and Applications|
|Depositing User:||Professor Alberto Bemporad|
|Date Deposited:||29 Jul 2011 10:18|
|Last Modified:||16 Nov 2011 11:50|
Actions (login required)