Feedback Stabilization Over Signal-to-Noise Ratio Constrained Channels

• Published in: IEEE transactions on automatic control 2007-08, Vol.52 (8), p.1391-1403
• Main Authors: Braslavsky, J.H., Middleton, R.H., Freudenberg, J.S.
• Format: Article
• Language: English
• Subjects: Applied sciences; Channels; Communication channels; Communication system control; Computer science; control theory; systems; Constraints; Control system analysis; Control system synthesis; Control systems; Control theory; Control theory. Systems; Costs; Delay; Exact sciences and technology; Feedback; feedback communication; information rates; linear-quadratic-Gaussian control; networked control systems; Noise; Noise robustness; Output feedback; Performance analysis; Process control. Computer integrated manufacturing; Robust control; Robustness; Sampling methods; Signal to noise ratio; signal-to-noise ratio (SNR); Stabilization; State feedback; Studies
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2007.902739

There has recently been significant interest in feedback stabilization problems with communication constraints including constraints on the available data rate. Signal-to-noise ratio (SNR) constraints are one way in which data-rate limits arise, and are the focus of this paper. In both continuous and discrete-time settings, we show that there are limitations on the ability to stabilize an unstable plant over a SNR constrained channel using finite-dimensional linear time invariant (LTI) feedback. In the case of state feedback, or output feedback with a delay-free, minimum phase plant, these limitations in fact match precisely those that might have been inferred by considering the associated ideal Shannon capacity data rate over the same channel. In the case of LTI output feedback, additional limitations are shown to apply if the plant is nonminimum phase. In this case, we show that for a continuous-time nonminimum phase plant, a periodic linear time varying feedback scheme with fast sampling may be used to recover the original SNR requirement at the cost of robustness properties. The proposed framework inherently captures channel noise effects in a simple formulation suited to conventional LTI control performance and robustness analysis, and has potential to handle time delays and bandwidth constraints in a variety of control over communication links problems.