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DOE OSTI · 1515199

Distributed output-feedback model predictive control for multi-agent consensus

Copp, David A.·Vamvoudakis, Kyriakos G.·Hespanha, João P.
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Abstract

We introduce a distributed output-feedback model predictive control approach for achieving consensus among multiple agents. Each agent computes a distributed control action based on an output-feedback measurement of a local neighborhood tracking error and communicates information only to its neighbors, according to a communication network modeled as a directed graph. Each agent computes its distributed control action by solving a local min–max optimization problem that simultaneously computes a local state estimate and control input under worst-case assumptions on unmeasured input disturbances and measurement noise. Under easily verified controllability and observability assumptions, this distributed output-feedback model predictive control approach provides an upper bound on the group consensus error, thereby ensuring practical consensus in the presence of unmeasured disturbances and noise. A numerical example with four agents connected in a directed graph is demonstrated to illustrate the results.

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42 ENGINEERINGDistributed model predictive controlMoving horizon estimationMulti-agent consensusOutput-feedback

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Copp, David A., Vamvoudakis, Kyriakos G., Hespanha, João P.. 2019-04-29. Distributed output-feedback model predictive control for multi-agent consensus. https://doi.org/10.1016/j.sysconle.2019.04.005

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