Parameters for an electrochemistry-based Lithium-ion battery model are estimated using the
homotopy optimization approach. A high-fidelity model of the battery is presented based on …

A technique is introduced for identifying uncertain and/or unknown parameters of chaotic
and hyper-chaotic systems via using a synchronization-based parameter observer. The …

Abstract Neural Ordinary Differential Equations (NeuralODEs) present an attractive way to
extract dynamical laws from time series data, as they bridge neural networks with the …

In this paper, our objectives are to estimate the moments of inertia and reconstruct the inputs
of a two-link pendulum that models a human arm. A blind parameter identification routine to …

In this paper, adaptive–impulsive synchronization and parameters estimation of chaotic
systems only by using discontinuous drive signals are investigated. In the scheme proposed …

Dynamic models of physical systems often contain parameters that must be estimated from
experimental data. In this work, we consider the identification of parameters in nonlinear …

This study presents a new methodology that combines quantitative image analysis,
clustering, and statistical techniques to examine the 2D distribution of osteohistological …

Abstract Model-based control considers system dynamics to solve challenging control
problems; recently, the amount of activity in developing model-based controllers is growing …

The inverse eigenstructure assignment aims at computing the mass and stiffness
parameters, leading to the desired dynamic behaviour expressed in terms of some desired …

When applying the single shooting approach to solve nonlinear dynamic parameter
identification problems, difficulties like undesired minima can occur. To circumvent this, we …