Nonlinear system identification is an extremely broad topic, since every system that is not
linear is nonlinear. That makes it impossible to give a full overview of all aspects of the fi eld …

Recent results show that a predictive building automation can be used to operate buildings
in an energy and cost effective manner with only a small retrofitting requirements. In this …

Model-predictive control (MPC) has recently excited much interest as a new control
paradigm for non-domestic buildings. Since it is based on the notion of optimization, MPC is …

This article reviews the development of experiment design in the field of identification of
dynamical systems, from the early work of the seventies on input design for open loop …

This book enables readers to understand system identification and linear system modeling
through 100 practical exercises without requiring complex theoretical knowledge. The …

Predictive control in buildings has undergone an intensive research in the past years. Model
identification plays a central role in a predictive control approach. This paper presents a …

Model-based control design plays a key role in today's industrial practice, and industry
demands cuttingedge methods for identifying the necessary models. However, additional …

The objective of this paper is to apply the Virtual Reference Feedback Tuning (VRFT) to
Multiple-Input Multiple-Output (MIMO) control strategies in wastewater treatment plants …

Modeling dynamics is often the first step to making a vehicle autonomous. While on-road
autonomous vehicles have been extensively studied, off-road vehicles pose many …

We present a new method of identifying a specific module in a dynamic network, possibly
with feedback loops. Assuming known topology, we express the dynamics by an acyclic …