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Creators/Authors contains: "Bridgeman, Leila"

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  1. ; ; ; (, Systems & Control Letters)
    Free, publicly-accessible full text available May 1, 2026
  2. ; ; ; (, IEEE Control Systems Letters)
    Free, publicly-accessible full text available January 1, 2026
  3. ; (, PMLR)
    Invariant sets are essential for understanding the stability and safety of nonlinear systems. However, certifying the existence of a positive invariant set for a nonlinear model is difficult and often requires knowledge of the system’s dynamic model. This paper presents a data driven method to certify a positive invariant set for an unknown, discrete, nonlinear system. A triangulation of a subset of the state space is used to query data points. Then, linear programming is used to create a continuous piecewise affine function that fulfills the criteria of the Extended Invariant Set Principle by leveraging an inequality error bound that uses the Lipschitz constant of the unknown system. Numerical results demonstrate the program’s ability to certify positive invariant sets from sampled data. 
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    Accepted Manuscript Full Text Available
  4. ; ; (, IEEE)
    Full Text Available 
  5. ; ; ; (, IEEE Control Systems Letters)
    Full Text Available 
  6. ; ; (, 5th Annual Learning for Dynamics and Control Conference)
    Accepted Manuscript Full Text Available