DocumentCode :
630616
Title :
Distributed parameterized model predictive control of networked multi-agent systems
Author :
Droge, Greg ; Egerstedt, M.
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
2013
fDate :
17-19 June 2013
Firstpage :
1332
Lastpage :
1337
Abstract :
When considering a distributed control framework for a multi-agent system, care has to be taken to respect the limited information available to each agent as well as the amount of possible communication in the network. This presents difficulties in performing distributed model predictive control as an agent must typically be able to simulate its neighbors dynamics into the future. We present a framework based on parameterized feedback control laws which will allow a multi-agent system to perform distributed model predictive control. It enables both the simulation of neighbors´ states as well as the ability to minimize a collective cost in a distributed fashion. Moreover, given cost and dynamic dependencies between agents, we characterize the information that is needed by each agent to evaluate whether the optimization is feasible in a given network.
Keywords :
control system synthesis; distributed control; distributed parameter systems; feedback; multi-agent systems; networked control systems; predictive control; state estimation; distributed parameterized model predictive control; dynamic dependencies; neighbor dynamics simulation; neighbor state simulation; networked multiagent systems; parameterized feedback control laws; Multi-agent systems; Optimal control; Optimization; Orbits; Predictive control; Trajectory; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
ISSN :
0743-1619
Print_ISBN :
978-1-4799-0177-7
Type :
conf
DOI :
10.1109/ACC.2013.6580021
Filename :
6580021
Link To Document :
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