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Title: Sampling-based Methods for Computing Largest Tolerable Input Sets
Committee:
Dr. F. Zhang, Advisor
Dr, Malisoff, Co-Advisor
Dr. Coogan, Chair
Dr. Wardi
Abstract:
The objective of the proposed research is to develop an algorithm to compute largest tolerable input sets for continuous-time nonlinear systems. Tolerable input sets are closely related to the important concept of invariant sets, which are subsets of a system’s state space where trajectories can enter, but will never leave. The largest set of inputs for which a set is invariant is called a largest tolerable input set, and they can be used to characterize the robustness of an invariant set. The proposed algorithm will use a sampling-based technique that evaluates a system's dynamics at points in the state space, and it requires little knowledge of other properties of the dynamics. This algorithm is a foundational tool that can be applied to a variety of problems and techniques involving systems with complicated dynamics that would be difficult to study with traditional analytical tools.
