Entropy in Networked Control

Dear Colleagues,

Networked control systems are spatially-distributed systems in which the communication between sensors, controllers, and actuators is accomplished through a shared digital communication network. Examples can be found, e.g., in vehicle tracking, underwater communications, remote surgery, and space exploration. In the simplest model, the communication network is displayed as a rate-limited digital channel over which state information acquired by sensors is transmitted to a controller. The most fundamental problem in this context is to determine the smallest information rate above which a specified control objective can be achieved.

For linear systems, the data-rate theorem characterizes this infimal rate for various forms of stabilization as the sum of the open-loop unstable modes, or equivalently, as the entropy of the uncontrolled system. For nonlinear systems, dynamical entropy concepts also play a fundamental role in describing the data-rate limits for stabilization, estimation and related objectives. While such characterizations are mostly restricted to deterministic models, information-theoretic entropy concepts naturally show up in stochastic models which incorporate noise in different system components.

This Special Issue features research involving information-theoretic and/or dynamical concepts of entropy in the context of control under communication constraints. In addition, contributions related to the classical data-rate theorem are welcome.

Dr. Christoph Kawan
Guest Editor

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