The problem considered here involves a functional I subject to differential constraints, nondifferential constraints, and general boundary conditions. It consists of finding the state x(t), control u(t), and parameter $\pi$ so that the functional I is minimized, while the differential constraints, nondifferential constraints, and boundary conditions are satisfied to a predetermined accuracy. Here, I is a scalar, x an n-vector, u an m-vector, and $\pi$ a p-vector.
Four types of gradient-restoration algorithms are considered, and their relative efficiency in terms of the number of iterations for convergence and CPU time is evaluated. The algorithms considered are as follows: sequential gradient-restoration algorithm, complete restoration (SGRA-CR); sequential gradient-restoration algorithm, incomplete restoration (SGRA-IR); combined gradient-restoration algorithm, no restoration (CGRA-NR); and combined gradient-restoration algorithm, incomplete restoration (CGRA-IR).
| Identifer | oai:union.ndltd.org:RICE/oai:scholarship.rice.edu:1911/13854 |
| Date | January 1994 |
| Creators | Ko, Shuh-Hung |
| Contributors | Miele, Angelo |
| Source Sets | Rice University |
| Language | English |
| Detected Language | English |
| Type | Thesis, Text |
| Format | 106 p., application/pdf |
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