Model reduction of uncertain systems:approximation by uncertain system

Model reduction is well studied and its use is very common for fixed-coefficients systems. Physical world, however, poses more sophisticated kind of problems: uncertainties in physical parameters cause the system model to have uncertain parameters. In this paper we propose a novel method for model reduction of discrete-time uncertain SISO systems. The meaning of model reduction for uncertain systems is defined in the paper. Then, the problem is formulated as a linear semi-infinite programming problem, which significantly reduces the computational complexity. A numerical example shows very good results.