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Multi-Agent Model Predictive Control: A Survey


Rudy Negenborn, Bart De Schutter, Hans Hellendoorn
Delft Center for Systems and Control,
Delft University of Technology

Technical report 04-010, Dec. 2004


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Already back in 1978, Sandell et al. surveyed a wide range of alternative methods for decentralized control. They found that a good combination of engineering judgment and analysis can be used to define in a reasonable way an adhoc control structure for a dynamic system. They conclude that methodologies are needed that present a designer with several good control structure candidates for further consideration.

In this report we look at how research since 1978 has advanced distributed control. We consider the control of large-scale systems like power networks, traffic networks, digital communication networks, exible manufacturing networks, ecological systems, etc. In particular, we survey some of the literature on Model Predictive Control (MPC) in distributed settings. We will refer to this as Multi-Agent Model Predictive Control. We are interested in the control design methods that have been developed so far.

The structure of this reported is as follows. In order to classify and nd structure in the literature on multi-agent MPC, in Section 2 we first consider control methodologies in general. Control methodologies involve different kinds of models. Depending on the actual models chosen, different issues rise that have to be considered. In Section 3 we focus on Model Predictive Control (MPC). We explain the general idea behind MPC and characterize the MPC framework in terms of the models of Section 2. As it turns out, the standard MPC framework may be seen as single-agent MPC. In Section 4 we move on to the discussion of multi-agent MPC.We refer to multi-agent MPC as a general term for methods that apply the MPC strategy using multiple agents to control a system. Important aspects of multi-agent MPC are the way in which a system is decomposed into subsystems (centralized, decentralized, hierarchical), the way in which control problems are formulated on these decomposed systems (centralized, decentralized, hierarchical), and the way in which agents communicate with one another in order to solve these control problems. We describe how recent literature on multi-agent MPC implements these issues. Finally, we end this report with open issues and concluding remarks in Section 5.


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