This thesis examines the neurobiological components of the motor control system and relates it to current control theory in order to develop a novel framework for models of motor control in the brain. The presented framework is called the Neural Optimal Control Hierarchy (NOCH). A method of accounting for low level system dynamics with a Linear Bellman Controller (LBC) on top of a hierarchy is presented, as well as a dynamic scaling technique for LBCs that drastically reduces the computational power and storage requirements of the system. These contributions to LBC theory allow for low cost, high-precision control of movements in large environments without exceeding the biological constraints of the motor control system.
| Identifer | oai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/4949 |
| Date | 13 January 2010 |
| Creators | DeWolf, Travis |
| Source Sets | University of Waterloo Electronic Theses Repository |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
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