Stabilization of Linear Systems Over Gaussian Networks

• Published in: IEEE transactions on automatic control Vol. 59; no. 9; pp. 2369 - 2384
• Main Authors: Zaidi, Ali A., Oechtering, Tobias J., Yüksel, Serdar, Skoglund, Mikael
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Channels; Controllers; Frame relay; Gaussian; Gaussian relay channels; Linear systems; moment stabilization; Network topology; networked control systems; Networks; Nickel; Noise measurement; Policies; Power plants; Relays; Remote control; Sensors; Silicon; Stabilization; networked control systems; linear systems; Gaussian relay channels; moment stabilization
• ISSN: 0018-9286; 1558-2523; 1558-2523
• DOI: 10.1109/TAC.2014.2322213

The problem of remotely stabilizing a noisy linear time invariant plant over a Gaussian relay network is addressed. The network is comprised of a sensor node, a group of relay nodes and a remote controller. The sensor and the relay nodes operate subject to an average transmit power constraint and they can cooperate to communicate the observations of the plant's state to the remote controller. The communication links between all nodes are modeled as Gaussian channels. Necessary as well as sufficient conditions for mean-square stabilization over various network topologies are derived. The sufficient conditions are in general obtained using delay-free linear policies and the necessary conditions are arrived at using information theoretic tools. Different settings where linear policies are optimal, asymptotically optimal (in certain parameters of the system) and suboptimal have been identified. For the case with noisy multidimensional sources controlled over scalar channels, it is shown that linear time varying policies lead to minimum capacity requirements, meeting the fundamental lower bound. For the case with noiseless sources and parallel channels, nonlinear policies which meet the lower bound have been identified.