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# Data-Driven Distributed Predictive Control via Network Optimization

*Proceedings of the 2nd Conference on Learning for Dynamics and Control*, PMLR 120:838-839, 2020.

#### Abstract

We consider a networked linear system where system matrices are unknown to the individual agents but sampled data is available to them. We propose a data-driven method for designing a distributed linear-quadratic controller where agents learn a non-parametric system model from a single sample trajectory in which nodes can predict future trajectories using only data available to themselves and their neighbors. Based on this system representation, we propose a control scheme where a network optimization problem is solved in a receding horizon manner. We show that the proposed control scheme is stabilizing and validate our results through numerical experiments.