Reinforcement Learning based Distributed Control of Dissipative Networked Systems

We consider the problem of designing distributed controllers to stabilize a class networked systems, where each subsystem is dissipative and designs reinforcement learning based local controller maximize an individual cumulative reward function. develop approach that enforces dissipativity conditions on these at guarantee stability entire system. The proposed illustrated DC microgrid example, objective maintain voltage network using generation unit.