Engineering Commons^™

A Dynamic Neural Network Designed Using Analytical Methods Produces Dynamic Control Properties Similar To An Analogous Classical Controller, Wade William Hilts, Nicholas Szczecinski, Roger Quinn, Alexander Hunt

Mechanical and Materials Engineering Faculty Publications and Presentations

Human balance is achieved using many concurrent control loops that combine to react to changes in environment, posture, center of mass and other factors affecting stability. Though numerous engineering models of human balance control have been tested, no methods for porting these models to a neural architecture have been established. It is our hypothesis that the analytical methods we have developed, combined with classical control techniques will provide a reasonable starting point for developing dynamic neural controllers that can reproduce classical control capabilities. In previous work, we tested this hypothesis and demonstrated that a biologically-constrained neural controller that replicates human …