A linear matrix inequality approach to robust H∞ filtering

We consider the robust H_∞ filtering problem for a general class of uncertain linear systems described by the so-called integral quadratic constraints (IQCs). This problem is important in many signal processing applications where noise, nonlinearity, quantization errors, time delays, and unmodeled dynamics can be naturally described by IQCs. The main contribution of this paper is to show that the robust H∞ filtering problem can be solved using linear matrix inequality (LMI) techniques, which are numerically efficient owing to recent advances in convex optimization. The paper deals with both continuous and discrete-time uncertain linear systems