Optimal design of stochastic networked control systems

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The goal of the proposed research is to advance the understanding of networked and cooperative control systems under uncertainty and information constraints. Stochastic networked control systems arise in many practical settings (such as in decentralized and adaptive power regulation in the energy/power grid, automotive applications for collision avoidance, sensor networks and in economics theory). However, there are many fundamental and practical aspects yet to be understood regarding such systems. The proposed research will have three main technical and practical contributions: (i) Development of a quantitative theory on the performance of decentralized dynamic systems given information constraints. This will lead to design principles for practical systems and infrastructure design for a large variety of applications. (ii) Stochastic stability of complex connected systems through event-driven communications and development of stochastic drift criteria for stability of such systems. This is important for decentralized systems which can only communicate when resources are available. (iii) Generation of approximately optimal control policies when controllers are able to learn the dynamics of a system through partial information or training sequences. This is especially important in cognition and learning aspects of controllers for adapting to an unknown environment in which they live and act. The outcomes will allow for the design of adaptive, cognitive and resource-efficient decentralized and networked control systems. In addition to fundamental contributions on theoretical problems regarding decision making under uncertainty, the research outcomes will have important practical impact in the technology sector in Canada and beyond, in view of optimal engineering system design for networked control systems under information constraints. In addition, four PhD, two MSc and two undergraduate students will be trained rigorously under this proposal, and be independent researchers who will benefit Canada's research and technological community.