The objective of this work is to generate new fundamental science for cyber-physical systems (CPSs) that enables more accurate and faster trajectory synthesis for controllers with nonlinear plants, or nonlinear constraints that encode obstacles. The approach is to utilize hybrid control to switch between models whose accuracy is normalized by their computational burden. This synergistic approach is why we deem our proposed work will enable Computationally Aware Cyber-Physical Systems.

Abstract: This poster summarizes our recently awarded grant on computationally aware cyber-physical systems (CPSs). The objective of this project is to generate new fundamental science for CPSs that enables more accurate and faster trajectory synthesis for controllers with nonlinear plants, or nonlinear constraints that encode obstacles. The approach is to utilize hybrid control to switch between models whose accuracy is normalized by their computational burden.