Deep reinforcement learning for scheduling in large-scale networked control systems

conference paper Deep reinforcement learning for scheduling in large-scale networked control systems published Adrian Redder author 52265https://orcid.org/0000-0001-7391-4688 Arunselvan Ramaswamy author 66937https://orcid.org/ 0000-0001-7547-8111 Daniel Quevedo author 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems - NECSYS 2019 Computing Resources Provided by the Paderborn Center for Parallel Computing project This work considers the problem of control and resource allocation in networked systems. To this end, we present DIRA a Deep reinforcement learning based Iterative Resource Allocation algorithm, which is scalable and control-aware. Our algorithm is tailored towards large-scale problems where control and scheduling need to act jointly to optimize performance. DIRA can be used to schedule general time-domain optimization based controllers. In the present work, we focus on control designs based on suitably adapted linear quadratic regulators. We apply our algorithm to networked systems with correlated fading communication channels. Our simulations show that DIRA scales well to large scheduling problems. https://ris.uni-paderborn.de/download/13443/13444/ifacconf.pdf application/pdf 2019Chicago, USA eng Networked control systemsdeep reinforcement learninglarge-scale systemsresource schedulingstochastic control Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems A. Redder, A. Ramaswamy, D. Quevedo, in: Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems, 2019. @inproceedings{Redder_Ramaswamy_Quevedo_2019, title={Deep reinforcement learning for scheduling in large-scale networked control systems}, booktitle={Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems}, author={Redder, Adrian and Ramaswamy, Arunselvan and Quevedo, Daniel}, year={2019} } Redder, Adrian, et al. “Deep Reinforcement Learning for Scheduling in Large-Scale Networked Control Systems.” Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems, 2019. Redder, A., Ramaswamy, A., & Quevedo, D. (2019). Deep reinforcement learning for scheduling in large-scale networked control systems. In Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems. Chicago, USA. A. Redder, A. Ramaswamy, and D. Quevedo, “Deep reinforcement learning for scheduling in large-scale networked control systems,” in Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems, Chicago, USA, 2019. Redder, Adrian, Arunselvan Ramaswamy, and Daniel Quevedo. “Deep Reinforcement Learning for Scheduling in Large-Scale Networked Control Systems.” In Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems, 2019. Redder A, Ramaswamy A, Quevedo D. Deep reinforcement learning for scheduling in large-scale networked control systems. In: Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems. ; 2019. 134432019-09-23T16:00:58Z2022-01-06T06:51:36Z