Set Descriptions of White Noise and Worst Case Induced Norms

Abstract

This paper provides a framework for analyzing white noise disturbances in linear systems. Rather than the usual stochastic approach, noise signals are described as elements in sets and the disturbance rejection properties of the system are described in a worst case setting. This type of modeling of noise and disturbances very much fits the philosophy of both the behavioral and robust control settings. The description is based on properties of finite records of signals, which may be verified directly on experimental data. Bounds of system gain for input signals in these sets are given, and their asymptotic behavior for long data records is analyzed.