This note extends previous results pertaining to algebraic state and parameter estimation of
linear systems based on a special construction of kernel system representations that …

It is shown how the kernel approach to joint parameter and state estimation can be improved
to handle large measurement noise. High accuracy of estimation results from combining the …

Previous results pertaining to algebraic state and parameter estimation of linear systems
based on a special construction of a forward-backward kernel representation of linear …

The concept of non-asymptotic state and parameter estimation is now gaining interest as the
development of more efficient control technologies poses new challenges. Hybrid or …

This note explains the advantage of employing integral system representations of linear
systems in application to state and input estimation for a broad class of LPV systems …

An efficient approach adopting Reproducing Kernel Hilbert Space, RKHS, to estimate the
parameters of Differential Equations from noisy realizations of the system's output is …

A kernel-based approach is explored to enhance robustness of flatness-based nonlinear
tracking control design for a synchronous generator machine. The design involves full …

Dynamical systems are found in almost every field, and Ordinary differential equations
(ODEs) are often used to model these systems. By solving the ODE, we can predictthe …

Non-asymptotic observers have received a great deal of attention in recent times due to the
advancement in hybrid control system theory. This is because fast and switching control …