Observability is a property of a dynamical system that defines whether or not it is possible to
reconstruct the trajectory temporal evolution of the internal states of a system from a given …

In this article, a unified identification framework called constrained subspace method for
structured state-space models (COSMOS) is presented, where the structure is defined by a …

This paper considers the identification of a network consisting of discrete-time LTI systems
that are interconnected by their unmeasurable states. For a large-scale network, the …

This article presents a systematic algorithm to select a set of auxiliary measurements in
order to consistently identify certain transfer functions in a dynamic network from …

Complex, dynamical systems, often of a high order, composed of several interconnected
subsystems, are referred to as large-scale systems (LSSs). This article presents a survey of …

The identification of local modules in dynamic networks with known topology has recently
been addressed by formulating conditions for arriving at consistent estimates of the module …

Dynamic networks are interconnected dynamic systems with measured node signals and
dynamic modules reflecting the links between the nodes. We address the problem of …

This article addresses the problem of consistently identifying a single transfer function in a
network of dynamic systems using only observational data. It is assumed that the topology is …

It poses significant challenge to control Hammerstein–Wiener systems involving modeling
nonlinearities. In this paper, a novel data-driven predictive control method based on the …

This manuscript details and extends the system identification methods leveraging the
backpropagation (SIMBa) toolbox presented in previous work, which uses well-established …