Graduate school in Systems, Optimization, Control and Networks (SOCN)

 

Graduate school courses scheduled in the academic year

2009-2010

 

Fall 2009


"MODEL PREDICTIVE CONTROL"
Lecturer : Jan MACIEJOWSKI
(University of Cambridge, UK)

 

 

Spring 2010

 

"COMPLEX NETWORKS : STRUCTURE AND DYNAMICS "
Lecturer : Santo FORTUNATO (ISI Foundation, Torino, Italy)

 

"MODELLING, ESTIMATION AND CONTROL OF BIOSYSTEMS "
Lecturers : Philippe BOGAERTS (ULB), Denis DOCHAIN (UCL), Alain VANDE WOUWER (FPMs), Jan VAN IMPE (KUL)

 

"LMI OPTIMIZATION WITH APPLICATIONS IN CONTROL"
Lecturer : Didier HENRION (LAAS-CNRS, Toulouse, France)

 

 


 

 

Detailed contents

 

 

1. MODEL PREDICTIVE CONTROL

 

Lecturer : Jan MACIEJOWSKI (University of Cambridge, UK)

 

Description

 

Model Predictive Control (MPC) is the only `advanced’ control methodology (ie more advanced than PID) which has found wide application in the process industries. It offers advantages which make it very attractive for other industries too, such as automotive and aerospace, and its use in such industries is being actively explored at present.

 

Contents

 

The course will start with the basic ideas of MPC, together with some specific examples of its advantages over “classical” control. It will then discuss the structure of MPC controllers, present possible variations (such as non-quadratic cost functions and stabilised predictions), and deal with important practicalities, especially disturbance feedforward and disturbance modelling. A state-space framework will be used, but the connection with the well-known GPC framework will be made. The course will then survey the state of recent MPC-related research, covering efficient computation, stability and robustness, prioritisation of objectives, the use of nonlinear models, the application of MPC to hybrid systems (which contain logic or mode switches as well as continuous dynamics), and distributed MPC. The course will be illustrated throughout with examples from various applications.

 

The course will be presented over 6 3-hour sessions, each session consisting of 2 lectures.

 

Session 1:

1. Introduction: Motivation, Basic ideas. Motivation: Industrial success of MPC; reasons for this success; examples of applications; future applications. Basic ideas: Receding horizon, reference trajectory, coincidence points, offset-free tracking, use with unstable plant. A little history.

2. Basic formulation and solution of MPC. Formulation: Linear model, quadratic cost, linear constraints. Prediction, disturbance models and observers. Examples. Solution: QP. Brief presentation of active set and interior point methods. Efficient ordering of variables. Constraint softening. Examples. Structure of MPC controller: Piecewise-affine.

 

Session 2:

3. The GPC formulation. Prediction using transfer functions. Prediction with a disturbance model. The GPC model. State-space interpretation.

4. Introduction to MPC Toolbox and hands-on experience.

 

Session 3:

5. Other formulations. Feedforward from measured disturbances. Stabilised predictions. Non-quadratic cost (1-norm or infinity-norm) - motivation and solution. Zones, funnels,coincidence points. PFC.

6. Stability. Strategies for ensuring stability: terminal constraints; infinite horizons; contraction conditions. Feasibility implies stability. Detailed presentation of Rawlings-Muske approach to infinite horizons in presence of constraints.

 

Session 4:

7. Tuning. Special cases: `Mean-level control', `Deadbeat control', `Perfect control'. Tuning parameters: Horizons, weights, disturbance model, observer.

8. Robust MPC; Uncertainty models: Norm-bounded; polytopes. Lee-Yu tuning; LQG-LTR tuning; relations to industrial practice. Outline of LMI approach to robust constrained MPC. Output admissible sets, positive-invariant sets, etc. Optimising over feedback policies instead of open-loop actions.

 

Session 5:

9. Two case studies. Shell heavy oil fractionator. Newell and Lee evaporator.

10. Hands-on experience with case-studies.

 

Session 6:

11. Nonlinear MPC. Using nonlinear internal models: pros and cons. Approximate solution using repeated relinearisation. Strategies for handling nonlinear internal models. Cost reduction rather than minimization.

12. Perspectives. Exploiting spare degrees of freedom - ideal resting values, fault-tolerance; Constraint management; Mixed Logic Dynamic (MLD) systems; links to hybrid control.

 

Supporting material

 

The course will be based on Prof. Maciejowski’s book “Predictive Control with Constraints” (Prentice-Hall, 2001, ISBN 0 201 39823 0) but will also contain some more recent material.

 

Dates : September 30 and october 01, 02, 19, 20, 21, 2009

Schedule : 09h15-12h15

 

Local : Auditorium Arenbergkasteel KAST01.07

 

!!! ATTENTION 01 october 15h00 - 18h00 Room 00.24 Dept of Electrical Engineering

 

This course will take place at the Katholieke Universiteit Leuven,
Department Elektrotechniek ESAT, Kasteelpark Arenberg 10, 3001 Heverlee

 

 

2.COMPLEX NETWORKS : STRUCTURE AND DYNAMICS

 

Lecturers : Santo FORTUNATO (ISI Foundation, Torino, Italy)

Description :

 

The modern science of networks is perhaps the most popular and promising research area within
complex systems.
Many systems can be represented as networks, but the latter are characterized by a set of
common statistical
regularities, which are crucial to understand their structure and function.

 

 

Contents :

 

The course will be divided into 6 sessions of 2 and a half hours each.

 

Session 1:

Networks: definitions, characteristics, basic concepts in graph theory, centrality measures,
weighted graphs

 

Session 2:

Real World Networks: examples, small-world properties, clustering coefficient,
fat-tailed degree distributions

 

Session 3:

Network models: Erdoes-Renyi graphs, models based on preferential
attachment, other models

 

Session 4:

Community structure I: elements of community structure, basic problems and
classical methods

 

Session 5:

Community structure II: new methods, modularity, testing and significance of
clustering

 

Session 6:

Dynamics on networks: resilience/percolation, epidemic spreading, social dynamics,
navigation, synchronization

 

Dates : February 02, 03, 05, 16, 17, 19, 2010.

 

Schedule : 09h15-12h15

 

 

Support : paper 1

 

Lecture I, Lecture II, Lecture III, Lecture IV, Lecture V, Lecture VI.

 

 

This course will take place at CESAME, Bâtiment Euler, 4, av. G. Lemaître, 1348 Louvain-la-Neuve

 

 

 

3.MODELLING, ESTIMATION AND CONTROL OF BIOSYSTEMS

Lecturers : Philippe BOGAERTS (ULB), Denis DOCHAIN (UCL), Alain VANDE WOUWER (FPMs), Jan VAN IMPE (KUL)

 

Course description :

 

Aim : The objective of this course is to give an introduction and cover recent aspects of dynamical modeling, monitoring and control of biochemical processes. The course will cover the following topics :

 

Dynamical modeling of biochemical processes : the notion of reaction networks and mass balance modeling will be introduced and used to build a general dynamical model for bioprocesses, both stirred tank reactors (described by ODE’s (ordinary differential equations)) and incompletely mixed reactors, such as fixed bed or fluidised bed reactors as well as population balance models (described by PDE’s (partial differential equations)). Mathematical concepts of the general dynamical model, including model reduction and stability, as well as microbial ecology concepts like the competitive exclusion principle, will be studied. The link with metabolic engineering will also be explicated. The course will also cover the identification of bioprocess models (including the structural and pratical model identifiability and the design of optimal experiments for parameter estimation). It will also address simulation issues related to PDE models and the use of reduction methods for this type of models.

 

Monitoring : this part of the course will be dedicated to the design applications of state observers (Luenberger observers, Kalman filters, asymptotic observers, robust observers, …) and parameter estimation algorithms (in particular to estimate reaction rates and yield coefficients).

 

Control : the course will emphasize optimal control and (adaptive) linearizing control (including adaptive extremum seeking). The choice of these control approaches will be motivated in the context of bioprocess applications.

 

Several practical applications will be used to illustrate the techniques and principles covered in this course. Examples will include problems from the food industry and the pharmaceutical industry to the environment and the (waste) water treatment.

 

 

Contents :

 

Module

Themes

duration

S1

Biosystem Modeling : introduction, model classes, property analysis

1.5h

S1

Parameter identification (I)

1.5h

S2

Parameter identification (II)

2h

S2

Optimal experiment design

1h

S3

State estimation

3h

S4

An overview of applications (food engineering, population models, microbial ecology, environmental processes, biotech industries)

2h

S4

Numerical simulation (with introduction to PDEs)

1h

S5

process optimization (optimal control and adaptive extremum seeking)

3h

S6

 

Control in practice: successful and not so succesful approaches with emphasis on batch and fed-batch applications

3h

 

Dates : March 15, 16, 17, 2010.

 

Schedule : 09h15 - 12h15 and 14h - 17h

 

ATTENTION !! On March 15 the course will begin at 9h00 until 12h00 and 14h00 until 17h00.

 

This course will take place at CESAME, Bâtiment Euler, 4, av. G. Lemaître, 1348 Louvain-la-Neuve

 

Support :

D. Dochain : 

 

A. Vande Wouwer, Ph. Bogaerts :

 

4. LMI OPTIMIZATION WITH APPLICATIONS IN CONTROL

 

Lecturer : Didier HENRION (Laas CNRS-Toulouse, FRANCE)

 

Description

 

This is a course for graduate students or researchers with a background in linear control systems, linear algebra and convex optimization.

The focus is on semidefinite programming (SDP), or optimization over linear matrix inequalities (LMIs), an extension of linear programming to the cone of positive semidefinite matrices. Since the 1990s, LMI methods have found numerous applications mostly in combinatorial optimization, systems control and signal processing.

Contents


Slides in PDF format will be posted here soon. See here for the last versions of the slides.

The course starts with fundamental mathematical features of linear matrix inequalities:

 

Homework :


Homeworks are handed out during the course. Some of this material is used during the labs. Full written solutions to the homeworks and labs (with Matlab scripts) are available on request.


Dates : April 26, 27, 28 and May 03, 04, 05, 2010

 

Schedule :

Monday : 14:00 - 17:30

Tuesday and Wednesday : 9:00 - 12:30

 

This course will take place at the Katholieke Universiteit Leuven, Thermotechnisch Instituut, Kasteelpark Arenberg 41, room 01.02 (Aula van de tweede hoofdwet), 3001 Heverlee

 

Support : 

Part 1.0 - Part 1.1 - Part 1.2 - Part 1.3 - Part 1.4 - Part 1.5 - Part 1.6
Part 2.1 - Part 2.2 - Part 2.3 - Part 2.4

 

 

Other courses scheduled in the academic year 2009-2010

 

 

5. NUMERICAL OPTIMAL CONTROL ALGORITHMS, AND APPLICATIONS IN RENEWABLE

ENERGY SYSTEMS

 

Lecturers : Moritz DIEHL (KUL, Leuven, Belgium) and B. HOUSKA(KUL, Leuven, Belgium)

 

Professor Responsible : Prof. Dr. Moritz Diehl

Telephone : 003216321884 Fax : Email :moritz.diehl@esat.kuleuven.be

Objectives :

Aim of the very interactive course is to provide the participants with a

strong working knowledge about the methods and applications of dynamic

optimization in engineering applications.

 

 

Programme to be followed :

 

The course will consist of lectures, interactive sessions and guided computer exercises.

Applications from several fields are treated in self-chosen tutorial

projects by the participants in the last two days of the course.

Particular emphasis is put on renewable

energy systems like wind power, seasonal heat pumps, or solar thermal

power plants.

 

A tentative list of treated topics is: Dynamic system modelling for

optimization, theory of nonlinear programming and optimal control,

dynamic programming, indirect versus direct approaches, simultaneous vs.

sequential approaches, parameter estimation and nonlinear least squares

problems, model

predictive control, application in chemical and mechanical engineering.

The software tool to be used is the open source tool ACADO - a toolkit for

automatic control and dynamic optimization.

 

Towards the end of the course every participant will be working on

formulating and solving a dynamic optimization problem of her/his own

choice, so it is encouraged to think about interesting applications of

dynamic optimization even before the course. The lectures and exercises

will be given by the organizers.

 

Minimum year of study: 4 th and 5 th year

Minimum level of English : high

 

Key words : numerical mathematics, optimization, direct optimal control methods, object oriented programming, interest in real world applications, dynamic system modeling,

Language (in which the Course will be taught) : English

Minimum : (Number of students required for the course to take place) : 10

Maximum : ( Total number of places, Home & non Home students, not to be exceeded) 30

Reserved for local Home students :  ( This total is included in the Maximum number of places) 5

 

Prerequisites :

 

This course is aimed at 4th or 5th year master students with very strong

skills in mathematics and a working knowledge of programming in C and

MATLAB. Strong knowledge of analysis and linear algebra (2 years) is

Requested and knowledge of numerical mathematics is very helpful.

 

Course exam :

 

A short written exam for self-assessment and rehearsal will be held on Friday morning

and the remaining time is devoted to individual computer projects performed by the participants.

 

Dates : November 16-20, 2009

 

Schedule :

 

09:00 - 12:30 & 14:00 - 18:00 except for friday 14:00 - 16:00

 

This course will take place at the Katholieke Universiteit Leuven, Celestijnenlaan 200C, room 00.04, 3001 Heverlee

 

 

 

6. NONLINEAR OBSERVER DESIGN : A DISSIPATIVE APPROACH

 

Lecturer : Jaime MORENO (UNAM, MEXICO)

 

Objectives :

In this seminar an overview of different nonlinear observer design problems and methods will be given. Then a dissipative framework for observer design, proposed recently by the author, will be discussed. It will be shown that the dissipative approach allows to unify and generalize several current design strategies. The general ideas will be illustrated with simulation examples, as well as with specific real-life applications.

 

The general objective of this minicourse (10 hours) is to give, first, a brief overview of different nonlinear observer design problems and methods. Then a recent approach for observer design, based on the dissipativity theory, will be presented and discussed. It will be shown that this dissipative approach unifies and generalizes several current design strategies. The general ideas will be illustrated with examples and possible applications for control.

 

Contents :

 

The course is divided in 4 sessions:

 

Dates : December 1 and 3, 2009

 

Schedule : 10:00 - 12:00 and 14:00 - 17:00.

 

Schedule : Auditorium of Service d'Automatique, 31 Boulevard Dolez, 7000 Mons (1st floor left).

 

This course will take place at Service d'Automatique of the Faculté Polytechnique de Mons, Bd Dolez 31, 7000 MONS

 

 

 

7.BELGIAN FRANCQUI CHAIR 2009-2010 - PAUL VAN DOOREN


Prof
.dr. Paul Van Dooren (Université Catholique de Louvain) has been awarded the Belgian Francqui Chair 2009-2010. As holder of this chair he will present at the University of Antwerp the lecture series "Matrix methods for systems and control". The lecture series commences on Monday, April 19, 2010 at 3.30 p.m. with the inaugural lecture "From Gauss to Google: why matrices matter". Rector Alain Verschoren and prof.dr. Herwig Leirs (dean Faculty of Sciences) are pleased to invite you to this occasion. The inaugural lecture will take place at G.010-Jan Fabre Auditorium, building G, Campus Middelheim, Middelheimlaan 1, Antwerp. You can

The lecture series continues with

Friday, April 23, 2010: Distance problems, spectra and pseudospectra.
Friday, April 30, 2010: Model reduction of dynamical systems.
Friday, May 07, 2010: Dominant feature extraction and structured matrices.

Friday, May 21, 2010: Networks and graphs.

All these lectures are delivered from 2 to 5.30 p.m. in room G.005 at Campus Middelheim including a coffee/tea break. Please confirm also your attendance at these lectures with Martine Vermeiren. Further information is provided on the attached flyer and can be obtained from prof.dr. Karel In ´t Hout (karel.inthout@ua.ac.be).



You can register for this occasion before April 1 by email to Martine Vermeiren (martine.vermeiren@ua.ac.be), mentioning the number of participants.


 

 

 

Registration

You can register electronically by filling in the following form via the web :

http://www.uclouvain.be/sites/socn/graduate_registration.html

If you have problems with this, please contact Nathalie PONET

The admission is free for doctoral students and participants from Belgian academic institutions. Other participants are requested to pay a registration fee of EURO 500,- per course but a waiver can be obtained under special conditions (contact the secretariat).
Payment can be made by bank transfer to the account n°310-0959001-48 with the mention "AUTO2866 ACTIVITES DIDACTIQUES"

 

Secretariat

Nathalie PONET
CESAME - Bât. Euler
4, av. G. Lemaître
1348 Louvain-la-Neuve (Belgium)

 

Tél : 010/47 80 36

fax : 010/ 47 21 80

e-mail : nathalie.ponet@uclouvain.be

web site : http://www.uclouvain.be/sites/socn