System Identification in Dynamic Networks

System Identification in Dynamic Networks

Dankers, A.G.

Van den Hof, P.M.J. (promotor)

Mechanical, Maritime and Materials Engineering

Delft Center for Systems and Control

2014-09-04

Systems in engineering such as power systems, telecommunication systems, and distributed control systems are becoming more complex and interconnected. Many of these systems are part of the foundation of modern society and their seamless operation is paramount. However, the increasing complexity and size of the systems poses real engineering challenges (in maintaining stability of the electrical power grid, increasing data throughput of telecommunication networks, etc.). These systems cannot be operated, designed, and maintained without the help of models. System identification is the art of constructing a model of a system from a given set of measurements. However, the field of system identification is primarily focused on identifying open and closed-loop systems. Recently, there has been a move to considering more complex interconnection structures, enabling the application of system identification tools to a larger variety of systems. In this thesis methods to consistently identify modules embedded in a dynamic network with known interconnection structure (topology) are developed. Thus, for example, using the tools developed in this thesis it is possible to estimate the dynamics of a power station (or an aggregate of generators such as wind, solar, etc.) given measurements taken during regular operation of the power grid. The resulting model enables operators of the grid to make better informed decisions and predictions about the grid. The tools developed in this thesis are quite general can be applied under a wide variety of conditions (such as the presence of process noise and sensor noise for instance). Consequently, it is expected that these methods can even be applied to a large variety of systems outside the engineering domain such as biological and geological systems.

system identification
dynamic networks
graph theory
identifiability
linear systems

https://doi.org/10.4233/uuid:cb7f49da-8c2e-4370-bc6b-80af0684e372

9789461863522

Institutional Repository

doctoral thesis

(c) 2014 Dankers, A.G.