Optimization-Based Actuator and Communication Scheduling in Networked Distributed Processes with Communication Delays

This work addresses the problem of control actuator and communication scheduling in spatially-distributed processes with discrete and delayed sensor-controller communication over a resource-constrained network. We focus on systems modeled by uncertain highly-dissipative Partial Differential Equations (PDEs) with low-order dominant dynamics. A finite-dimensional model-based controller with an embedded propagation unit that compensates for the communication delay is initially designed and the feasible ranges of control actuator locations and sensor-controller communication rates are explicitly characterized in terms of the communication delay. This characterization is used to formulate and solve a receding-horizon model-based optimization problem, subject to delay-dependent stability constraints, which yields the optimal control actuator and sensor-controller communication schedules that optimize the closed-loop performance and network resource utilization simultaneously. The developed methodology is illustrated through an application to a simulated diffusion-reaction process.