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LQG Control and Sensing Co-Design by Tzoumas, Vasileios; Carlone, Luca; Pappas, George J.; Jadbabaie, Ali is a scholarly article available to read on EtoBox.

What is LQG Control and Sensing Co-Design about?

We investigate a Linear-Quadratic-Gaussian (LQG) control and sensing co-design problem, where one jointly designs sensing and control policies. We focus on the realistic case where the sensing design is selected among a finite set of available sensors, where each sensor is associated with a different cost (e.g., power consumption). We consider two dual problem instances: sensing-constrained LQG control, where one maximizes control performance subject to a sensor cost budget, and minimum-sensing LQG control, where one minimizes sensor cost subject to performance constraints. We prove no polynomial time algorithm guarantees across all problem instances a constant approximation factor from the optimal. Nonetheless, we present the first polynomial time algorithms with per-instance suboptimality guarantees. To this end, we leverage a separation principle, that partially decouples the design of sensing and control. Then, we frame LQG co-design as the optimization of approximately supermodular set functions; we develop novel algorithms to solve the problems; and we prove original results on the performance of the algorithms, and establish connections between their suboptimality and contro

Author

Tzoumas, Vasileios; Carlone, Luca; Pappas, George J.; Jadbabaie, Ali

Published

2018

Language

EN