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A Gain Scheduling Optimization Method Using Genetic Algorithms, Robert C. Martin Iv
A Gain Scheduling Optimization Method Using Genetic Algorithms, Robert C. Martin Iv
Theses and Dissertations
Gain scheduling. the traditional method of providing adaptive control to a nonlinear system, has long been an ad hoc design process. Until recently; little theoretical guidance directed this practitioners' art. For this reason a systematic study of this design process and its potential for optimization has never been accomplished. Additionally, the nonlinearities and the large search space involved in gain scheduling also precluded such an optimization study. Traditionally, the gain scheduling process has been some variation of a linear interpolation between discrete design points. By using powerful non-traditional optimization tools such as genetic algorithms there are ways of improving this …
Predicting Protein Structure Using Parallel Genetic Algorithms, George H. Gates Jr.
Predicting Protein Structure Using Parallel Genetic Algorithms, George H. Gates Jr.
Theses and Dissertations
The protein folding problem is a biochemistry Grand Challenge problem. The challenge is to reliably predict natural three-dimensional structures of polypeptides. Genetic algorithms (GAs) are robust, semi-optimal search techniques modeling natural evolutionary processes. Fast messy GAs (fmGAs) are variants of messy GAs that reduce the exponential time complexity to polynomial. This investigation evaluates the merits of parallel SGAs and fmGAs for minimizing the potential energy of a pentapeptide, (Met)-enkephalin. AFIT's energy model is compared to a similar model in a commercial package called QUANTA. Differences between the two models are identified and resolved to enhance GAs' abilities to correctly fold …
A Genetic Algorithm Approach To Automating Satellite Range Scheduling, Donald A. Parish
A Genetic Algorithm Approach To Automating Satellite Range Scheduling, Donald A. Parish
Theses and Dissertations
Satellite range scheduling involves scheduling satellite supports in which a satellite and a specific remote tracking station communicate with each other within a specified time window. As the number of satellite supports continue to increase, more pressure is placed on the current manual system to generate schedules efficiently. Previous research efforts focused on heuristic and mixed-integer programming approaches which may not produce the best results. The objective of this research was to determine if a genetic algorithm approach to automating the generation of 24 hour schedules was competitive with other methods. The goal was to schedule as many supports as …