Scalable Algorithms for Physical Systems

We are seeking to develop more reliable algorithms for use with physical systems of varying dimensionality. Using these algorithms, we address issues of computational complexity and resource management in the design of algorithms for information determination, control, and sensitivity analysis which remain applicable to complicated nonlinear and impulsive systems. Our projects involve distributed control theory, hybrid control, sensitivity minimization, impacting systems, and information determination in continuous systems.

Detailed project information is available at the following links:

Robotic Marionettes

Sensitivity Minimization

Control of Impacting Systems

Fisher Information Analysis
and Optimization

Hybrid Control

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