Abstract
In this chapter we propose a distributed model predictive control scheme based on agent negotiation. In particular, we consider the control of several subsystems coupled through the inputs by a set of independent agents that are able to communicate and we assume that each agent has access only to the model and the state of one of the subsystems. This implies that in order to take a cooperative decision, i.e. for the whole system, the agents must negotiate. At each sampling time, following a given protocol, agents make proposals to improve an initial feasible solution on behalf of their local cost function, state and model. These proposals are accepted if the global cost improves the cost corresponding to the current solution. In addition, we study the stability properties of the proposed distributed controller and provide precise conditions that guarantee that the closed-loop system is practically stable along with an optimization based controller and invariant design procedure.
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Notes
- 1.
The symbol “\(*\)” stands for the symmetric part of a matrix.
References
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Acknowledgments
Financial support from the HYCON2 EU-project from the ICT-FP7 and MEC-Spain, DPI2008-05818, and F.P.I. grants is gratefully acknowledged.
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Maestre, J.M., Muñoz de la Peña, D., Camacho, E.F. (2014). Distributed MPC Based on Agent Negotiation. In: Maestre, J., Negenborn, R. (eds) Distributed Model Predictive Control Made Easy. Intelligent Systems, Control and Automation: Science and Engineering, vol 69. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7006-5_29
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DOI: https://doi.org/10.1007/978-94-007-7006-5_29
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