LPT-2011-08 BibTeX
@ARTICLE{LPT-2011-08,
AUTHOR = {I. Alvarado and D. Limon and D. Munoz de la Pena and J.M. Maestre and M.A. Ridao and H. Scheu and W. Marquardt and R.R. Negenborn and B. De Schutter and F. Valencia and J. Espinosa},
TITLE = {{A comparative analysis of distributed MPC techniques applied to the HD-MPC four-tank benchmark}},
JOURNAL = {Journal of Process Control},
YEAR = {2011},
volume = {21},
number = {5},
pages = {800-815},
month = {},
note = {},
abstract = {Recently, there has been a renewed interest in the development of distributed model predictive control (MPC) techniques capable of inheriting the properties of centralized predictive controllers, such as constraint satisfaction, optimal control, closed-loop stability, etc. The objective of this paper is to design and implement
in a four-tank process several distributed control algorithms that are under investigation in the research groups of the authors within the European project HD-MPC. The tested controllers are centralized and decentralized model predictive
controllers schemes for tracking and several distributed MPC schemes based on (i) cooperative game theory, (ii) sensivity-based coordination mechanisms, (iii) bargaining game theory, and (iv) serial decomposition of the centralized problem.
In order to analyze the controllers, a control test is proposed and a number of performance indices are defined. The experimental results of the benchmark provide an overview of the performance and the properties of several state-of-the-art distributed predictive controllers.
},
keywords = {Distributed control, Predictive control, Optimal control, Benchmark examples, Control applications},
}
I. Alvarado, D. Limon, D. Munoz de la Pena, J.M. Maestre, M.A. Ridao, Holger Scheu, Wolfgang Marquardt, R.R. Negenborn, B. De Schutter, F. Valencia, J. Espinosa:
A comparative analysis of distributed MPC techniques applied to the HD-MPC four-tank benchmark
Journal of Process Control, 2011, 21(5), 800-815
Abstract:
Recently, there has been a renewed interest in the development of distributed model predictive control (MPC) techniques capable of inheriting the properties of centralized predictive controllers, such as constraint satisfaction, optimal control, closed-loop stability, etc. The objective of this paper is to design and implement
in a four-tank process several distributed control algorithms that are under investigation in the research groups of the authors within the European project HD-MPC. The tested controllers are centralized and decentralized model predictive
controllers schemes for tracking and several distributed MPC schemes based on (i) cooperative game theory, (ii) sensivity-based coordination mechanisms, (iii) bargaining game theory, and (iv) serial decomposition of the centralized problem.
In order to analyze the controllers, a control test is proposed and a number of performance indices are defined. The experimental results of the benchmark provide an overview of the performance and the properties of several state-of-the-art distributed predictive controllers.
Keywords:
Distributed control, Predictive control, Optimal control, Benchmark examples, Control applications