Title
Distributed model predictive control of nonlinear systems subject to delayed measurements
Abstract
In this work, we focus on distributed model predictive control of nonlinear systems subject to delayed measurements. Delayed measurements arise naturally in process control applications when, for example, species concentrations or particle size distributions are measured. We design distributed Lyapunov-based model predictive controllers that coordinate their actions and take delayed measurements explicitly into account. Sufficient conditions under which the proposed distributed control design guarantees that the state of the closed-loop system is ultimately bounded in a region that contains the origin are provided. The applicability and effectiveness of the proposed control method is illustrated through a chemical process example.
Year
DOI
Venue
2009
10.1109/CDC.2009.5400774
CDC
Keywords
Field
DocType
particle size distributions,control system synthesis,closed loop system,lyapunov-based model predictive controllers,distributed control design,nonlinear systems,distributed control,delayed measurements,species concentrations,process control applications,closed loop systems,lyapunov methods,predictive control,nonlinear system,actuators,process control,sensors,trajectory,stability analysis,particle size distribution
Lyapunov function,Mathematical optimization,Nonlinear system,Work in process,Computer science,Control theory,Model predictive control,Distributed model predictive control,Trajectory,Actuator,Bounded function
Conference
ISSN
ISBN
Citations 
0191-2216 E-ISBN : 978-1-4244-3872-3
978-1-4244-3872-3
1
PageRank 
References 
Authors
0.41
10
3
Name
Order
Citations
PageRank
Jinfeng Liu126528.37
David Muñoz de la Peña229324.98
Panagiotis D. Christofides378492.67