2 papers
eess.SY2026
Input-to-State Stable Bundle Koopman Neural ODEs for Learning Controlled Dynamics under Environmental Constraints
Lin Feng
We propose ISS-BKNO, a unified framework that integrates Koopman operator identification, Neural ordinary differential equations (ODEs), fiber bundle geometry, and input-to-state s…
eess.SY2026
Safe Data-Driven Control and Dynamical Learning via Constrained Neural Architectures and Koopman Operators
Lin Feng, Xin He
The deployment of learning-based models in safety-critical control systems demands mathematical guarantees that standard regression architectures cannot provide. This paper present…