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  <title><![CDATA[Ph.D. Proposal Oral Exam - Jesse Paul Varnell]]></title>
  <body><![CDATA[<p><strong>Title:&nbsp; </strong><em>Sampling-based Methods for Computing Largest Tolerable Input Sets</em></p>

<p><strong>Committee:&nbsp; </strong></p>

<p>Dr. F. Zhang, Advisor</p>

<p>Dr, Malisoff, Co-Advisor&nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</p>

<p>Dr. Coogan, Chair</p>

<p>Dr. Wardi</p>

<p><strong>Abstract: </strong></p>

<p>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&rsquo;s state space where trajectories can enter, but will never leave.&nbsp; 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.&nbsp; The proposed algorithm will use a sampling-based technique that evaluates a system&#39;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.</p>
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