19D051TOS - Optimization techniques in control and decision systems

Course specification
Course title Optimization techniques in control and decision systems
Acronym 19D051TOS
Study programme Electrical Engineering and Computing
Module System Control and Signal Processing
Type of study doctoral studies
Lecturer (for classes)
Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
      ESPB 9.0 Status elective
      Condition none
      The goal The aim of the course is to Introduce the students with advanced optimization techniques, which means getting acquainted with the theoretical foundations of the most common methods, formulating practical optimiyation problems in accordance with the these techniques and analysis of the possibility of applying these methods to practical problems.
      The outcome Within this course, students will master the following skills: analysis of real optimization problems and their mathematical formulation so that they are suitable for the application of mathematical optimization methods; analysis of the application of adequate algorithms in accordance with the requirements of the problem; application of learned optimization techniques and solution analysis.
      Contents of lectures Convex sets and functions. Duality theory. Convex optimization (linear programming, semidefinite optimization, geometric programming). Non-convex optimization (Gradient Descent, Newton method, Stochastic gradient descent, Bayesian optimization). Integer programming. Stochastic programming. Dynamic programming. Extremum seeking.
      Contents of exercises none
      1. Boyd, S. P. Convex Optimization. Cambridge University Press, 2004 (Original title)
      2. Snyman J. A., Wilke D. N. Practical mathematical optimization. Springer Science+ Business Media, Incorporated, 2005. (Original title)
      3. Bellman R. E., Dreyfus S. E. Applied dynamic programming. Princeton University Press, 2015 (Original title)
      4. Beck, A. First-Order Methods in Optimization. Society for Industrial and Applied Mathematics, 2017 (Original title)
      5. Ariyur, K. B., Krstic M. Real-time optimization by extremum-seeking control. John Wiley & Sons, 2003. (Original title)
      Number of hours per week during the semester/trimester/year
      Lectures Exercises OTC Study and Research Other classes
      Methods of teaching 8x15 hours of lectures
      Knowledge score (maximum points 100)
      Pre obligations Points Final exam Points
      Activites during lectures 0 Test paper 0
      Practical lessons 0 Oral examination 30
      Projects 70
      Colloquia 0
      Seminars 0