An upper bound of the worst-case Hankel norm for systems with non-memoryless uncertainty

The Hankel norm plays a crucial role in approximating systems with reduced order systems. The Hankel norm has been usually dealt with for given transfer functions. However, since uncertainty is often involved in most models of real systems, the worst-case Hankel norm is required to evaluate approximation errors. The paper proposes an upper bound of the worst-case Hankel norm for systems with uncertainty. In particular, the paper deals with non-memoryless uncertainty, while existing upper bounds have been given for memoryless uncertainty