A realization of Gromov's nonsqueezing theorem and its applications to uncertainty analysis in Hamiltonian systems are studied in this paper. Gromov's nonsqueezing theorem describes a fundamental property of symplectic manifolds, however, this theorem is usually started in terms of topology and its physical meaning is vague. In this paper we introduce a physical interpretation of the linear symplectic width, which is the lower bound in the nonsqueezing theorem, given the eigenstructure of a positive-definite, symmetric matrix. Since a positive-definite, symmetric matrix always represents the uncertainty ellipsoid in practical mechanics problems, our study can be applied to uncertainty analysis. We find a fundamental inequality for the evolving uncertainty in a linear dynamical system and provide some numerical examples.
Proceedings of the American Control Conference, 2006, 6p.