5 papers
Adaptive Stability-Constrained Neural Differential Equations for Controlled Dynamical Systems with Unknown Inputs
Syed Pouladi
Continuous-time neural models are attractive for identifying nonlinear systems, but a small one-step error can grow rapidly when a learned vector field is rolled out under inputs t…
Learning Stable Controlled Dynamical Systems via Input-Contraction Neural Differential Models
Syed Pouladi
Learning continuous-time representations of dynamical systems from observation data has emerged as a cornerstone of data-driven control and scientific machine learning. However, ex…
Stable Fiber-Koopman Residual Dynamics for Environment-Constrained Robust Control
Syed Pouladi
Learning-based dynamical models face a persistent tension between expressiveness and formal guarantees: richer model classes improve predictive accuracy, but their stability proper…
Stability-Certified Koopman Observer Design for Nonlinear Systems via Generalized Persidskii Dynamics
Syed Pouladi
This paper addresses the problem of nonlinear state estimation for dynamical systems whose governing equations are approximated through Koopman operator liftings. While Koopman-bas…
Stability Analysis and Data-Driven State Estimation for Generalized Persidskii Systems with Time Delays: Theory and Experimental Validation on PMSM Drives
Syed Pouladi
This paper addresses the stability analysis and state estimation of generalized Persidskii systems subject to time-varying delays and external disturbances. The generalized Persids…