Analysis and control of distributed parameter systems

linma2300  2020-2021  Louvain-la-Neuve

Analysis and control of distributed parameter systems
Due to the COVID-19 crisis, the information below is subject to change, in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
5 credits
30.0 h + 30.0 h
Dochain Denis;
Main themes
The content of this course deals with the control of linear time invariant systems. In particular the notions of dynamical models and feedback loop will be considered. The notion of operator (implicitly connected to Laplace transform) will be used to transform differential equations into algebraic equations in order to introduce the concept of transfer functions that will ease the analysis and synthesis of controllers and closed-loop systems. The course will mainly concentrate on PID (proportional-integral-derivative) controllers, with reference to the IMC (internal model control) approach which is largely used in process control. The course will also consider topics like time-delay compensation, feedforward actions, ratio control and cascade control, and is open to topics like inferential control and state observers. The course is based in particular on the notions of mass and energy balances and of unit operations, and it is illustrated by examples drawn from applications in the process industry.

At the end of this learning unit, the student is able to :

1 With respect to the referentiel AA, this courses contributes to the dvelopment,  the acquisition and the evaluation of the following learning outcomes :
  • AA1.1, AA1.2, AA1.3
  • AA5.3, AA5.4, AA5.5
At the end of this course, the student will be able :
  •  to define a control problem poser;
  • to define the important variables related to the control problem;
  • to derive the mathematical model suited to the design of the controller;
  • to analyzer the control problem;
  • to select and synthesize  an appropriate control strategy;
  • to evaluate the performance of the selected control strategy
  1. General concepts of  control
  2. Notions of dynamical balances
  3. Mathematical models of dynamical  systems
  4. Stability
  5. Steady-state acurracy
  6. Disturbance rejection and trajectory tracking
  7. Robustness
  8. Control structures
  9. Case studies, in particular from the process industry
Teaching methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

The course consists of ex-cathedra courses and of pracical exercices aimed at implementing the concepts of the course in particular via computer exercices using Matlab and Simulink as well as  two laboratories aimed at implementing the basic concepts  (dynamics and PID regulation)  of the course on a tank level control system.
The presence at the laboratories are mandatory ; the registration is done via a piece of paper posted at the level -1 of the Euler building . Both laboratories  will the object of an individual evaluation performed during the last week of the semester.
Three homeworks are proposed during the semester. These are individual works proposing the solution of exercices illustrating the matter of the course. These have to be hand-written. Typically two weks are given before the delivery of the homeworks. The homeworks are mandatory. Any delay in the delivery of homeworks will generate a note of 0/20.
Evaluation methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

Possible laboratory evaluation outside of the exam period and report of maximum 25 pages on one application related to the scope of the course and covering different aspects of the course matter.
Manuel : notes de cours, notice de laboratoire, articles scientifiques de référence et (parties d')ouvrages de référence (disponibles sur moodle).
Faculty or entity

Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Master [120] in Chemical and Materials Engineering

Master [120] in Electro-mechanical Engineering

Master [120] in Mathematical Engineering

Master [120] in Biomedical Engineering