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Ecole nationale supérieure de l'Énergie, l'Eau et l'Environnement
Engineering school in energy, water and environment
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> Studies > E3-STU-COURSES

Advanced Control : Methods and Practical Implementation Tools - 5EUS5AUA

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  • Number of hours

    • Lectures : 26.0
    • Tutorials : -
    • Laboratory works : 34.0
    • Projects : -
    • Internship : -
    ECTS : 5.0
  • Officials : Christophe BERENGUER


The aim of this course is to present advanced control systems methods for optimal and predictive control and fault detection and isolation & fault tolerance. Tools and methods for real-time implementation of control algorithms on embedded systems are also presented


1) Predictive control : Illustrative example ; Prediction equations for linear time invariant systems ; Definition of the cost function ; Link with the unconstrained optimal regulator ; Constraints definition ; Constrained predictive control ; Control parametrization ; Application examples ; Nonlinear Predictive control
2) Model-based Diagnosis : Introduction, basic concepts, motivation and preliminaries: fault detection and isolation and its use for fault-tolerance and complex systems monitoring and safety. Process models and fault modelling. Presentation of the different approaches and focus on the model-based approach. ; Data validation and reconciliation: measurement errors, balance equations, state estimation for constrained and unconstrained systems, linear and bilinear systems ; Fault detection with parity equations - Static and dynamic cases: Analytical redundancy, parity equations and generation of residuals. Enhanced and structured residuals. Properties and analysis of residual signals ; Fault detection and isolation with state observers and state estimation. Unknown inputs observers. Observers banks.

3) Embedded system code design & implementation : Real-time and Embedded Systems design : Real-Time scheduling algorithms on uni and multiprocessor systems, programming techniques


Basic course in control systems, scientific programming and real-time computer systems


Session 1 : 60%CT + 40% CC
Session 2 : R Remplace CT

CC 40% + CT 60%

The exam is given in english only FR


The course exists in the following branches:

see the course schedule for 2019-2020

Additional Information

Course ID : 5EUS5AUA
Course language(s): FR FR

You can find this course among all other courses.


1) R. Isermann, Fault-Diagnosis Systems - An Introduction from Fault Detection to Fault Tolerance. Springer, 2006.
2) E. F. Camacho and C.Bordons Alba, Model Predictive Control, Springer 2004.
3)M. Alamir, A Pragmatic Story of Model Predictive Control: Self-Contained algorithms and case-studies, CreateSpace, 2013.

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Date of update February 8, 2017

Grenoble INP Institut d'ingénierie Univ. Grenoble Alpes