Information-constrained Optimal Control of Distributed Systems with Power Constraints
It provides a tractable solution for optimal control of interconnected systems under communication delays and power constraints, which is relevant for networked control systems.
This paper solves the LQG optimal control problem for distributed systems with one-step communication delays and power constraints by reformulating it as a linear covariance problem and exploiting zero-duality gap to decompose it into sub-problems, enabling offline computation of optimal control gains.
In this paper we address the problem of information-constrained optimal control for an interconnected system subject to one-step communication delays and power constraints. The goal is to minimize a finite-horizon quadratic cost by optimally choosing the control inputs for the subsystems, accounting for power constraints in the overall system and different information available at the decision makers. To this purpose, due to the quadratic nature of the power constraints, the LQG problem is reformulated as a linear problem in the covariance of state-input aggregated vector. The zero-duality gap allows us to equivalently consider the dual problem, and decompose it into several sub-problems according to the information structure present in the system. Finally, the optimal control inputs are found in a form that allows for offline computation of the control gains.