Decentralized MPC of nonlinear systems: An input-to-state stability approach

This paper presents stabilizing decentralized model predictive control (MPC) algorithms for discrete‐time nonlinear systems. The overall system under control is composed by a number of subsystems, each one locally controlled with an MPC algorithm guaranteeing the input‐to‐state stability (ISS) prope...

Full description

Saved in:
Bibliographic Details
Published in:International journal of robust and nonlinear control 2007-11, Vol.17 (17), p.1651-1667
Main Authors: Raimondo, D.M., Magni, L., Scattolini, R.
Format: Article
Language:English
Subjects:
decentralized control
input-to-state stability
nonlinear model predictive control
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents stabilizing decentralized model predictive control (MPC) algorithms for discrete‐time nonlinear systems. The overall system under control is composed by a number of subsystems, each one locally controlled with an MPC algorithm guaranteeing the input‐to‐state stability (ISS) property. Then, the main stability result is derived by considering the effect of interconnections as perturbation terms and by showing that also the overall system is ISS. Both open‐loop and closed‐loop min–max formulations of robust MPC are considered. Copyright © 2007 John Wiley & Sons, Ltd.
ISSN:1049-8923
1099-1239
DOI:10.1002/rnc.1214