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Massachusetts Institute of Technology

Global dynamic optimization

Abstract

dc:description.abstract

(cont.) on a set composed of the Cartesian product between the parameter bounds and the state bounds. Furthermore, I show that the solution of the differential equations is affine in the parameters. Because the feasible set is convex pointwise in time, the standard result that a convex function composed with an affine function remains convex yields the desired result that the integrand is convex under composition. Additionally, methods are developed using interval arithmetic to derive the exact state bounds for the solution of a linear dynamic system. Given a nonzero tolerance, the method is rigorously shown to converge to the global solution in a finite time. An implementation is developed, and via a collection of case studies, the technique is shown to be very efficient in computing the global solutions. For problems with embedded nonlinear dynamic systems, the analysis requires a more sophisticated composition technique attributed to McCormick. McCormick's composition technique provides a method for computing a convex underestimator for for the integrand given an arbitrary nonlinear dynamic system provided that convex underestimators and concave overestimators can be given for the states. Because the states are known only implicitly via the solution of the nonlinear differential equations, deriving these convex underestimators and concave overestimators is a highly nontrivial task. Based on standard optimization results, outer approximation, the affine solution to linear dynamic systems, and differential inequalities, I present a novel method for constructing convex underestimators and concave overestimators for arbitrary nonlinear dynamic systems ...

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Chemical Engineering.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2004

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Singer, Adam B
Advisor dc:contributor.advisor
  • Paul I. Barton.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
en_US

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/28662
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/28662

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Singer, Adam B. Global dynamic optimization. Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/28662