Abstract
In this study, a distributed extremum-seeking control approach is proposed to solve a class of constrained real-time optimization problems. Each agent operates over a sensor network. The agents have access to the measurement of a local cost and local constraints which it can communicate to neighbouring agents over the network. A dynamic consensus algorithm is used to provide all agents with an estimate of the total network cost and global constraints. A local extremum seeking controller is used to manipulate local input variables. It is shown that the distributed extremum-seeking control system achieves the optimization of the total network cost.
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