Identification of nonlinear continuous-time systems from noisy input–noisy output observations

Within the framework of the FWO research project G.0052.18N we are looking for two enthusiastic PhD researchers. The project starts on the 1st of January 2018 and consists of two 4 years PhD scholarships within the time span 2018-2023.

The research environment

The FWO research project fits within the main research activities of the department ELEC. The department ELEC has more than 35 years of experience in

  • Measurement and modelling of dynamical systems,
  • Developing fundamentally sound system identification tools, and 
  • Applying these identification tools to engineering problems in need of models


System identification is the engineering discipline which aims at constructing mathematical models of physical systems, based on measured data. The purpose of these estimated models can be very broad: to gain physical insights into the system, to build a robust controller, to detect anomalies, to compensate for unwanted behaviour, to predict future outcomes, etc...

Abstract of the FWO research project

In depth understanding of the complex dynamics of physical processes is the first step towards prediction (e.g. weather forecasting), control (e.g. driverless cars), and (computer aided) design (e.g. electronic circuits, drugs). These complex dynamics are often described by nonlinear differential equations with a priori unknown dynamic order, unknown parameters, and unknown nonlinear structure. The major objective of this project is to extract (estimate) the unknown/missing information from (well-designed) experiments. Therefore, a frequency domain system identification framework for estimating nonlinear differential equations from noisy input – noisy output observations will be developed that requires as little user interaction as possible. Such a nonlinear modelling framework is currently not available, while it has potential impact on very diverse scientific disciplines ranging from bio-mechanics, nonlinear modal analysis, to the characterization of material properties and growth modelling in economics.


You are a talented electrical or mechanical engineer at Master level. You have the intention to perform scientific research, in view of obtaining a PhD degree. You can work independently, and collaborate in a team on challenging problems. You are eager to learn, have good didactical skills and enjoy sharing your knowledge with students and peers. You are fluent in English, and a good knowledge of Dutch is an advantage.


Good basic knowledge on the following topics are required

  • System identification
  • System and control theory
  • Signal processing
  • Statistics
  • Linear algebra, complex analysis, Fourier and Laplace transforms
  • Hands on experience with Matlab
  • Good communication skills



Interested candidates should send a detailed CV along with a motivation letter to

John Lataire (John.Lataire [at]  and Rik Pintelon (Rik.Pintelon [at]

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