Nonstochastic information concepts for estimation and control

— Entropy and information are crucial notions in stochastic communication systems. However, they have arguably not been as central in control theory, which has a rich tradition of non-random models and techniques. This tutorial session aims to describe the key elements of certain non-probabilistic entropy and information concepts for state estimation and control. In this paper, which comprises the first half of the session, the focus is on a recently developed theory of nonstochastic information. Motivated by worst-case estimation and control, this framework allows non-statistical analogues of mutual independence, Markovness, information, and directed information to be rigorously defined. This yields powerful information-theoretic tools for finding fundamental bounds in zero-error communication and worst-case control systems. In the second half of this session, notions of entropy for deterministic nonlinear control systems are described, based on dynamical systems theory. These no...

• Type: Journal
• Year: 2015
• Where: CDC
• Authors: Girish N. Nair
• Keywords: CDC 2015, Control Systems