Fundamental constraints on uncertainty evolution in Hamiltonian Systems

[[abstract]]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.[[conferencetype]]國際[[conferencedate]]20060614~20060616[[iscallforpapers]]Y[[conferencelocation]]Minnesota, US

Sensitivity of Optimal Control Problems Arising from their Hamiltonian Structure

International audienceFirst-order necessary conditions for optimality reveal the Hamiltonian nature of optimal control problems. Regardless of the overwhelming awareness of this result, the implications that it entails have not been fully explored. We discuss how the symplectic structure of optimal control constrains the flow of sub-volumes in the phase space. Special emphasis is devoted to dynamics in the neighborhood of optimal trajectories and insight is gained into how errors in the initial states affect terminal conditions. Specifically, we prove that if the optimal trajectory does not satisfy a particular condition, then there exists a set of variations in the initial states yielding a greater error in norm when mapped to the terminal time through the state transition matrix. We relate this result to the sensitivity problem in solving indirect problems for optimal control

Computational Geometric Mechanics and Control of Rigid Bodies.

This dissertation studies the dynamics and optimal control of rigid bodies from two complementary perspectives, by providing theoretical analyses that respect the fundamental geometric characteristics of rigid body dynamics and by developing computational algorithms that preserve those geometric features. This dissertation is focused on developing analytical theory and computational algorithms that are intrinsic and applicable to a wide class of multibody systems. A geometric numerical integrator, referred to as a Lie group variational integrator, is developed for rigid body dynamics. Discrete-time Lagrangian and Hamiltonian mechanics and Lie group methods are unified to obtain a systematic method for constructing numerical integrators that preserve the geometric properties of the dynamics as well as the structure of a Lie group. It is shown that Lie group variational integrators have substantial computational advantages over integrators that preserve either one of none of these properties. This approach is also extended to mechanical systems evolving on the product of two-spheres. A computational geometric approach is developed for optimal control of rigid bodies on a Lie group. An optimal control problem is discretized at the problem formulation stage by using a Lie group variational integrator, and discrete-time necessary conditions for optimality are derived using the calculus of variations. The discrete-time necessary conditions inherit the desirable computational properties of the Lie group variational integrator, as they are derived from a symplectic discrete flow. They do not exhibit the numerical dissipation introduced by conventional numerical integration schemes, and consequently, we can efficiently obtain optimal controls that respect the geometric features of the optimality conditions. The approach that combines computational geometric mechanics and optimal control is illustrated by various examples of rigid body dynamics, which include a rigid body pendulum on a cart, pure bending of an elastic rod, and two rigid bodies connected by a ball joint. Since all of the analytical and computational results developed in this dissertation are coordinate-free, they are independent of a specific choice of local coordinates, and they completely avoid any singularity, ambiguity, and complexity associated with local coordinates. This provides insight into the global dynamics of rigid bodies.Ph.D.Aerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/60804/1/tylee_1.pd