• Slides  (pdf files)
  • Information on the course (2011-2012)
  • Optimization: Introduction
  • Linear programming
  • Quadratic programming
  • Nonlinear optimization without constraints
  • Nonlinear optimization with constraints
  • Convex optimization
  • Global optimization
  • Optimization: Summary
  • Matlab optimization toolbox
  • Multi-objective optimization
  • Integer optimization
  • The slides of the Control chapters can be downloaded from the Blackboard website of the course (registered users only)
  
  
• Sample exams:
  • Sample exam 1 and its Worked solutions
  • Sample exam 2 and its Worked solutions
  • Sample exam 3 and its Short solutions
  • Sample exam 4 and its Short solutions
  
  
• Exercises:
  • Excercises for Chapters 1-7 and 11 and Solutions of the exercises (last update: October 30, 2011; the differences with the previous versions are marked in color)


• Matlab m files for the examples in the lecture notes:
  • LP brewery example (p. 19-25, p. 89)
  • QP example 1 (p. 30)
  • QP example 2 (p. 31-32, p. 90)
  • simulated annealing example (p. 78)
  • MPC example (p. 91-93)
  • Neural network example (p. 99-104):
    main file: nnopt.m
    residuals and their Jacobian: nnfun.m
    initial estimates: nninit.m
    data: nndata.mat
  • Multi-criteria controller design: (chapter 14, p. 169-172)
    main file: mcd.m
    objective function: mcd_J.m
    constraints: mcd_con.m
  
  
• Practical exercise:
  • Description (2011-2012)
    Notes and hints:
    • The deadline for emailing the results for part A and B.3 to Bart De Schutter is Monday, October 17, 2011 at 17.00 pm.
    • In case you are not so familiar with discrete-time linear systems, the backward shift operator, etc. you may want to consult the mini lecture notes on "Discrete-time systems" that can be downloaded from the Blackboard pages of the course (under the item "Course materials", at the bottom of the page).
    • Note that for questions A.1 and A.2 of the assignment you are not expected to rewrite the transfer function expression by substituting the q operator or by creating one expression with a common denominator. In fact, for question A.1 we suggest you to first look at the structure of the expression for n^ and to note that we ask for convexity in terms of the variables a, b1, b2, e0, e1, and f. See also Question III of Sample exam 1.
      In case you still need an additional hint, start by looking at the first term only with ys(k)=1 for all k.
    
    
    
  • Data set for group 1 (R. Camillusson, G. Birpoutsoukis)
  • Data set for group 2 (S.H. Jang, C. Fuchs)
  • Data set for group 3 (F. Trink, M. Lakshmeesh)
  • Data set for group 4 (Y. Pan, P. Ramamurthy)
  • Data set for group 5 (B. Gunes, A. Aalbers)
  • Data set for group 6 (F. Almeida, N. Pereira)
  • Data set for group 7 (T. Kabos, L. Ottolini)
  • Data set for group 8 (S. van der Kleij, S. Burger)
  • Data set for group 9 (R. Molenaar, K. Kästner)
  • Data set for group 10 (T. Walvoort, J. van Ginkel)
  • Data set for group 11 (W. van Westering, M. Struijk)
  • Data set for group 12 (A. Vermeulen, J. van Doornik)
  • Data set for group 13 (R. Dev Sharma, C. Uribe)
  • Data set for group 14 (P.K. Gupta, C. Noorman)
  • Data set for group 15 (D. van Amstel, O.A. Ciftci)
  • Data set for group 16 (M. Kolsteeg, N. van Arnhem)
  • Data set for group 17 (H. Meijdam, )
  • Data set for group 18 (H. Dantas, D. Kuiper)
  • Data set for group 19 (M.M.H. Liu, T. Djojorahardjo)
  • Data set for group 20 (V. Goemans, K. Kuipers)
  • Data set for group 21 (N. van Duijkeren, W. Xiao)
  • Data set for group 22 (B. Koopman, C. van der Marel)
  • Data set for group 23 (S. Boersma, F. Hezel)
  • Data set for group 24 (A. Stoop, K. Nagaki)
  • Data set for group 25 (J. Postma, J. Domhof)
  • Data set for group 26 (W. van den Hof, S. van Ipenburg)
  • Data set for group 27 (M. Hajiahmadi, R. Verzijlbergh)
  • Data set for group 28 (Y. Zeinaly, Y. Wang)
  • Data set for group 29 (M. de Gier, E. de Gelder)
  • Data set for group 30 (G.J. Damsteegt, K. van der Mijle)
  • Data set for group 31 (N. van der Pas, J. Stapel)
  • Data set for group 32 (G. van der Weg, S. Fraling)
  • Data set for group 33 (H. Tol, M. Wiskemann)
  • Data set for group 34 (K. van Witteveen, C. Gevaerts)
  • Data set for group 35 (Y. Kocak, A. Koelewijn)
  • Data set for group 36 (M. Galrinho, P. Pereira)
  • Data set for group 37 (,)
  
  Note: download the .mat file, save it in the current matlab directory, and then in matlab use the command "load data_group_x.mat" to import the data from the .mat files (where x is your group number).