"An algorithm based on the mechanics of natural genetics is used to solve two different optimization problems. The algorithm combines survival of the fittest among string structures with randomized information exchange to form a search algorithm. Initiated with a population of bits-coded individuals, the genetic algorithm searches for the optimal solutions generation-by-generation. The three main operations in the genetic algorithm: Reproduction, Crossover, and Mutation give this algorithm the power of searching. In the first part of this thesis, the genetic algorithm is used to determine the optimal trajectories of the aeroassisted vehicle reentry problem. The trajectories to be optimized are determined not only by the parameter searching but also under a height constraint which make this study more interesting.
In the second part of this thesis the genetic algorithm is used for designing three-axis bang-bang controllers for the time-optimal rigid spacecraft reorientation problem. The firing times of the bang-bang controller and the time of rotation are determined by searching for the angular velocity thresholds and the reorientation time"--Abstract, page iv.
Balakrishnan, S. N.
Koval, Leslie Robert
Grow, David E.
Mechanical and Aerospace Engineering
M.S. in Aerospace Engineering
University of Missouri--Rolla
Journal article titles appearing in thesis/dissertation
Suboptimal atmospheric trajectory design using genetic algorithms with variable mutation
A variable mutation genetic algorithm for time-optical spacecraft reorientation controller design
xii, 116 pages
© 1994 Yao-Feng Cheng, All rights reserved.
Thesis - Restricted Access
Library of Congress Subject Headings
Space vehicles -- Control systems -- Computer simulation
Print OCLC #
Electronic OCLC #
Cheng, Yao-Feng, "Genetic algorithms for aeroassisted trajectory optimization and time-optimal spacecraft reorientation controller design" (1994). Masters Theses. 1348.
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