A subsystems approach for parameter estimation of ODE models of hybrid systems

TL;DR

This paper introduces a novel subsystem-based method for parameter estimation in ODE models of hybrid systems, enabling parallel processing and noise robustness, which improves efficiency and accuracy in system identification.

Contribution

The paper proposes a new approach that decomposes hybrid system ODE models into subsystems for parallel parameter estimation, handling noisy data effectively.

Findings

Method is easily parallelizable.

Handles noisy observational data.

Improves efficiency of parameter estimation.

Abstract

We present a new method for parameter identification of ODE system descriptions based on data measurements. Our method works by splitting the system into a number of subsystems and working on each of them separately, thereby being easily parallelisable, and can also deal with noise in the observations.