Rotating mechanical systems, electronic oscillators, cardiovascular
impedance measurements, etc. are examples of systems that exhibit
periodically time-varying behaviour. The dynamical behaviour of
these systems is usually studied using linear periodically time-varying
(LPTV) models for which many identification techniques have been
proposed during the last few decades. While being very effective and
accurate, it is not possible for these techniques to predict the
influence of system parameters (mechanical dimensions, circuit
component values, etc.) on the LPTV models. The main objective of
this junior post-doc is to develop scalable LPTV modelling techniques
that capture the variation of these LPTV models as a function of the
system parameters. Three electronic applications will be targeted to
showcase and validate the effectiveness of the developed
techniques. Taking into account variations of the system-specific
properties will significantly advance the state-of-the-art in LPTV
modelling. By doing so, future users in the design and control
community will have access to a powerful modelling framework for
the design and control of a variety of real-life periodically time-varying
Effective start/end date1/10/2030/09/21

    Research areas

  • Scalable models, linear periodically time-varying systems

    Flemish discipline codes

  • Computer aided engineering, simulation and design
  • Microwaves, millimeter waves and THz components and circuits and systems
  • Systems theory, modelling and identification
  • Numerical modelling and design
  • Signal processing not elsewhere classified

ID: 53377594