6 papers
Koopman Modeling and Stabilization of Discrete-Time Nonlinear Control Systems: Bilinearity on a Reproducing Kernel Hilbert Space
Jarod Morris, Xiuzhen Ye, Wentao Tang
Despite the popularity of Koopman modeling for nonlinear systems, in the presence of input variables, the evident nonexistence of a fully linear time-invariant model even in infini…
A constrained symbolic regression approach for Lyapunov function discovery
Ilias Mitrai, Wentao Tang
In this paper, we consider the data-driven discovery of Lyapunov functions for autonomous dynamical systems. We represent the Lyapunov function as an expression tree of fixed depth…
Neural Luenberger state observer for nonautonomous nonlinear systems
Moritz Woelk, Jarod Morris, Wentao Tang
This work proposes a method for model-free synthesis of a state observer for nonlinear systems with manipulated inputs, where the observer is trained offline using a historical or…
Koopman-based Estimation of Lyapunov Functions: Theory on a Reproducing Kernel Hilbert Space
Wentao Tang, Xiuzhen Ye
Koopman operator provides a general linear description of nonlinear systems, whose estimation from data (via extended dynamic mode decomposition) has been extensively studied. Howe…
Data-Driven State Observers for Measure-Preserving Systems
Wentao Tang
The use of data-driven control strategies on systems with not fully measurable states induces the problem of learning-based state observation. Motivated by this need, the present w…
Data-Driven Observer Synthesis for Autonomous Limit Cycle Systems through Estimation of Koopman Eigenfunctions
Angela Ni, Wentao Tang
The signal of system states needed for feedback controllers is estimated by state observers. One state observer design is the Kazantzis-Kravaris/Luenberger (KKL) observer, a genera…