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Model-Based and Data-Driven Fault Detection and Isolation

academic year

Course teacher(s)

Michel KINNAERT (Coordinator)

ECTS credits

See programme details

Language(s) of instruction


Course content

1. Generation of fault indicators

  • Parity space approach to the generation of fault indicators (or residuals)

  • Observer-based approach to residual generation

Both methods are developed in a deterministic and in a stochastic framework

2. Statistical change detection algorithms for decision system design

  • Introduction for statistical process control

  • Shewart and exponentially weighted moving average (EWMA) control chart

  • Cumulative sum (CUSUM) algorithm and generalized likelihood ration algorithm

3. Change detection based on parameter estimation methods

Objectives (and/or specific learning outcomes)

  • To master the principles of the design of fault detection and isolation systems, based on an mathematical model of the supervised process.

  • To get acquainted with some on-line change detection algorithms and to be able to use them in a decision system

Teaching methods and learning activities

The lectures alternate with implementation of the methods on simple case studies using the MATLAB/SIMULINK software.

Contribution to the teaching profile

This teaching unit contributes to the following competences:

  • In-depth knowledge and understanding of the advanced methods and theories to schematize and model complex problems or processes

  • Reformulate complex engineering problems in order to solve them (simplifying assumptions, reducing complexity)

  • Correctly report on research or design results in the form of a technical report or in the form of a scientific paper

  • Present and defend results in a scientifically sound way, using contemporary communication tools, for a national as well as for an international professional or lay audience

  • Work in an industrial environment with attention to safety, quality assurance, communication and reporting

  • Think critically about and evaluate projects, systems and processes, particularly when based on incomplete, contradictory and/or redundant information

  • A creative, problem-solving, result-driven and evidence-based attitude, aiming at innovation and applicability in industry and society

  • A critical attitude towards one’s own results and those of others

  • Consciousness of the ethical, social, environmental and economic context of his/her work and strives for sustainable solutions to engineering problems including safety and quality assurance aspects

  • The flexibility and adaptability to work in an international and/or intercultural context

  • An attitude of life-long learning as needed for the future development of his/her career

  • Has an active knowledge of the theory and applications of electronics, information and communication technology, from component up to system level.

  • Is able to analyse, specify, design, implement, test and evaluate individual electronic devices, components and algorithms, for signal-processing, communication and complex systems.

References, bibliography, and recommended reading

  • M. Basseville et I.V. Nikiforov (1993). Detection of Abrupt Changes: Theory and Applications, Prentice-Hall.

  • T. Soderstrom and P. Stoica (1989) System Identification. Prentice-Hall International.

  • M. Blanke, M. Kinnaert, J. Lunze et M. Staroswiecki (2015) Diagnosis and Fault Tolerant Control, 3rd Edition, Springer.

Other information


Service d'Automatique et d'Analyse des Systèmes, Buidling L, Door E, 2nd floor, email : michel.kinnaert@ulb.ac.be


Method(s) of evaluation

  • Oral examination

Oral examination

Oral examination

Mark calculation method (including weighting of intermediary marks)

  • Report on the practical work: 50%

  • Oral examination :50%

Language(s) of evaluation

  • english