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.