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Volume 12 Issue 12
Dec.  2025

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2025  >  12(12): 2572-2588
S. Talukder and R. Kumar, “Robust safety and stability of partially observed nonlinear systems with parametric variability,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 12, pp. 2572–2588, Dec. 2025. doi: 10.1109/JAS.2025.125837
Citation: S. Talukder and R. Kumar, “Robust safety and stability of partially observed nonlinear systems with parametric variability,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 12, pp. 2572–2588, Dec. 2025. doi: 10.1109/JAS.2025.125837
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Robust Safety and Stability of Partially Observed Nonlinear Systems With Parametric Variability

doi: 10.1109/JAS.2025.125837
Funds:  This work was supported in part by the National Science Foundation (CSSI-2004766, PFI-2141084, 2414972)
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    Abstract
  • Optimal output-feedback stabilization of nonlinear plants under variation of model parameters and partial observability of states is a challenging problem. Safety-critical applications face additional hurdles to preclude systems’ trajectories from encountering any unsafe state. To address these challenges, this paper extends a Lyapunov-based framework introduced recently for safety and stability-guaranteed neural network (NN)-based state-feedback control synthesis. In particular, here we propose a novel sufficient condition of the stabilizability of nonlinear partially observed systems under Lipschitz-bounded output-feedback controllers (OFCs), which generalizes such a condition proposed in the earlier work assuming full observability of states. A new algorithm is proposed that employs this newly devised condition to compute a maximal Lipschitz bound of OFCs and a corresponding maximal robust-safe-region-of-stabilization, enabling a safety and stability-guaranteed training of an NN-based optimal OFC by constraining the NN’s Lipschitz constant within the computed bound. The proposed method is validated using a numerical example and a single-generator-infinite-bus power system model.

     

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