An optimal control algorithm is proposed for impulsive differential systems, ie, systems
evolving according to ordinary differential equations between any two control actions …

The previously proposed Newton observer for nonlinear systems has fast exponential
convergence and applies to a wide class of problems. However, the Newton observer lacks …

This manuscript aims at develo** a nonlinear model predictive controller formulation
based on Carleman approximation. It approximates the nonlinear dynamic constraints with …

In this paper a mathematical tool is presented, to estimate unknown variables of transcription
networks, according to a set of measurements of the transcriptional activity of promoters. The …

This work investigates the state prediction problem for nonlinear stochastic differential
systems, affected by multiplicative state noise. This problem is relevant in many state …

Mathematical optimization problems are prevalent across various disciplines in science and
engineering. Particularly in electrical engineering, convex and non-convex optimization …

Continuous-discrete models refer to systems described by continuous ordinary or stochastic
differential equations, with measurements acquired at discrete sampling instants. Here we …

In this article, we consider the estimation problem of continuous-time stochastic systems with
discrete measurements, having linear drift and nonlinear diffusion term. We build the infinite …

The state estimation problem, here investigated, regards a class of nonlinear stochastic
systems, characterized by having the state model described through stochastic differential …

In order to improve the performance of analysis, it is important to consider the nonlinearity in
power system. The Carleman embedding technique (linearization procedure) provides an …