Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 18th IFAC World Congress |
| Publisher | IFAC Secretariat |
| Pages | 7987-7992 |
| Number of pages | 6 |
| Edition | 1 PART 1 |
| ISBN (print) | 9783902661937 |
| Publication status | Published - 2011 |
| Externally published | Yes |
Publication series
| Name | IFAC Proceedings Volumes (IFAC-PapersOnline) |
|---|---|
| Number | 1 PART 1 |
| Volume | 44 |
| ISSN (Print) | 1474-6670 |
Abstract
In this paper, we consider a general framework for distributed model predictive control (DMPC) of discrete-time nonlinear systems with decoupled dynamics, but subject to coupled constraints and a common, cooperative task. In contrast to most of the existing DMPC schemes in the literature, we do not necessarily consider the stabilization of an a priori known setpoint, but also other cooperative tasks like consensus and synchronization problems can be handled within the proposed framework. In order to ensure recursive feasibility and convergence to the desired cooperative goal, the systems optimize a local cost function in a sequential order, communicating their planned trajectories only to their neighbors. We exemplarily show how the proposed DMPC algorithm can be used for achieving consensus and synchronization between the systems, and we illustrate the results with a simulation example.
Keywords
- Distributed control, Nonlinear control, Predictive control, Stabilization, Synchronization
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
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Proceedings of the 18th IFAC World Congress. 1 PART 1. ed. IFAC Secretariat, 2011. p. 7987-7992 (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 44, No. 1 PART 1).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A general distributed MPC framework for cooperative control
AU - Müller, Matthias A.
AU - Reble, Marcus
AU - Allgöwer, Frank
N1 - Funding Information: ⋆ This work was supported by the German Research Foundation (DFG) within the Priority Programme 1305 “Control Theory of Digitally Networked Dynamical Systems” and within the Cluster of Excellence in Simulation Technology (EXC 310/1) at the University of Stuttgart.
PY - 2011
Y1 - 2011
N2 - In this paper, we consider a general framework for distributed model predictive control (DMPC) of discrete-time nonlinear systems with decoupled dynamics, but subject to coupled constraints and a common, cooperative task. In contrast to most of the existing DMPC schemes in the literature, we do not necessarily consider the stabilization of an a priori known setpoint, but also other cooperative tasks like consensus and synchronization problems can be handled within the proposed framework. In order to ensure recursive feasibility and convergence to the desired cooperative goal, the systems optimize a local cost function in a sequential order, communicating their planned trajectories only to their neighbors. We exemplarily show how the proposed DMPC algorithm can be used for achieving consensus and synchronization between the systems, and we illustrate the results with a simulation example.
AB - In this paper, we consider a general framework for distributed model predictive control (DMPC) of discrete-time nonlinear systems with decoupled dynamics, but subject to coupled constraints and a common, cooperative task. In contrast to most of the existing DMPC schemes in the literature, we do not necessarily consider the stabilization of an a priori known setpoint, but also other cooperative tasks like consensus and synchronization problems can be handled within the proposed framework. In order to ensure recursive feasibility and convergence to the desired cooperative goal, the systems optimize a local cost function in a sequential order, communicating their planned trajectories only to their neighbors. We exemplarily show how the proposed DMPC algorithm can be used for achieving consensus and synchronization between the systems, and we illustrate the results with a simulation example.
KW - Distributed control
KW - Nonlinear control
KW - Predictive control
KW - Stabilization
KW - Synchronization
UR - http://www.scopus.com/inward/record.url?scp=84864455958&partnerID=8YFLogxK
U2 - 10.3182/20110828-6-IT-1002.02884
DO - 10.3182/20110828-6-IT-1002.02884
M3 - Conference contribution
AN - SCOPUS:84864455958
SN - 9783902661937
T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)
SP - 7987
EP - 7992
BT - Proceedings of the 18th IFAC World Congress
PB - IFAC Secretariat
ER -