COVID-19 has disrupted normal life and has enforced a substantial change in the policies,
priorities and activities of individuals, organisations and governments. These changes are …

Bilinear system is a special class of nonlinear system. This paper is concerned with the
identification problem of the bilinear systems in the state–space form. By treating the …

Master Techniques and Successfully Build Models Using a Single Resource Vital to all data-
driven or measurement-based process operations, system identification is an interface that …

This paper is concerned with the parameter estimation of a general class of nonlinear
dynamic systems in state-space form. More specifically, a Maximum Likelihood (ML) …

Industrial data sets are often contaminated with outliers due to sensor malfunctions, signal
interference, and other disturbances as well as interplay of various other factors. The effect …

This paper develops and illustrates a new maximum-likelihood based method for the
identification of Hammerstein–Wiener model structures. A central aspect is that a very …

In this paper, the problems of parameter estimation are addressed for systems with scarce
measurements. A gradient-based algorithm is derived to estimate the parameters of the …

This paper proposes parameter estimation algorithms for Hammerstein nonlinear ARX
systems. By making full use of the current and previous input–output data of the system, a …

In this paper, we consider the parameter estimation issues of a class of multivariate output-
error systems. A decomposition based recursive least squares identification method is …

Gamification has become a significant direction in designing technologies, services,
products, organizational structures, and any human activities towards being more game-like …