Hyuk Park

Robust System Identification: Finite-sample Guarantees and Connection to Regularization

  • Hyuk Park
    • Categories Control Applications, Robust Optimization, Semi-definite Programming Tags , ,

    We address the problem of identifying a stable linear time-invariant system from a single sample trajectory. The least squares estimate (LSE) is a commonly used algorithm for this purpose. However, LSE may exhibit poor identification errors when the number of samples is small. To mitigate the issue, we introduce the robust LSE, which integrates robust … Read more

    Data-Driven Stochastic Dual Dynamic Programming: Performance Guarantees and Regularization Schemes

  • Hyuk Park
  • Zhuangzhuang Jia
  • Grani A. Hanasusanto
    • Categories Stochastic Programming Tags , , , ,

    We propose a data-driven scheme for multistage stochastic linear programming with Markovian random parameters by extending the stochastic dual dynamic programming (SDDP) algorithm. In our data-driven setting, only a finite number of historical trajectories are available. The proposed SDDP scheme evaluates the cost-to-go functions only at the observed sample points, where the conditional expectations are … Read more