The classical approach to motion control for nonlinear systems can be broken down into two independent steps. Path planning is done first, and then a tracking control law is found which guarantees that the system converges to the desired path. The goal of this research is to develop a unified framework in which to address the both the planning and the tracking problems for nonlinear systems. The strategy for accomplishing this research goal is to first quantify several characteristics of trajectories for nonlinear systems. Trajectory planning algorithms will then be developed for a broad class of nonlinear systems. Finally, the integration of feedback control with the planned trajectories will be examined, and algorithms will be developed for generating both the planning and tracking control laws. The results of this research will have a broad impact on the growing area of autonomous systems, allowing for better reactions to changing conditions such sensed obstacles or large disturbances. By considering the planning and tracking problems in an integrated fashion, paths can be generated that are "easy" for the system to follow: fast, robust, stable, and requiring minimum energy. The education plan for this project includes developing a set of web-based tutorials to teach students the importance and utility of system modeling concepts. By using powerful simulation software, nonlinear system models can be treated quite easily, and more realistic examples can be incorporated into system modeling courses.
