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U.S. Department of Energy
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Command generation by tree search in artificial intelligence

Thesis/Dissertation ·
OSTI ID:6093933

Investigation is made into treating the noncausal open-loop command generator for a totally automatic controller of the TAFCOS-type (which divides control effort into open-loop and closed-loop parts) as a heuristic tree-search problem in artificial intelligence. Discussion is given of earlier analytic dynamic-optimization and optimal-control approaches. It is the purpose of this work to create a software bed for achieving, in a command generator, heuristic open-loop control actions similar to humans, and thus to relieve downstream ignorant closed-loop controllers of responsibility for dealing with large errors. Emphasis is on an Edisonian - in contrast to a Newtonian - approach. Appendices contain a simple Riccati-equation solver, two different search prototypes in BASIC, and a more general tree=based command generator written in C, with a Users' Guide.

Research Organization:
Texas Tech Univ., Lubbock, TX (USA)
OSTI ID:
6093933
Country of Publication:
United States
Language:
English