Convex Optimization for Control, 9+3 credits
Course typeAdvanced course
Intended audienceStudents who want to get an introduction to
convex optimization with emphasis on applications in control.
ContentsThe course is based on material developed by Stephen Boyd
at Stanford University and Lieven Vandenberghe at UCLA. A more detailed
description of the contents is given in the schedule.
OrganizationThere will be 12 lectures. The students are expected
to participate in 4 exercise sessions, solve 2 home work problems and carry out
a non-mandatory project. There is a final exam. It is compulsory to attend the
lectures and the exercise sessions.
ScheduleFirst lecture is March 9, 15.15-17.00, Algoritmen, see detailed
LiteratureWe will mainly use the book Boyd, S. and L. Vandenberghe:
"Convex Optimization", Cambridge University Press, 2004. Additional references are
- A. Ben-Tal and A. Nemerovski, Lectures on Modern Convex Optimization
- Analysis, Algorithms, and Engineering Applications, MPS-SIAM Series on
- D. Bertsekas, Nonlinear Programming, Athena Scientific.
- D. Luenberger, Linear and Nonlinear Programming, Addison-Wesley.
- J. Nocedal and S. Wright, Numerical Optimization, Springer.
- H. Wolkowicz, R. Saigal, and L. Vandenberghe, Handbook of
Semidefinite Programming: Theory, Algorithms, and Applications, Kluwer
- S. Boyd, L. El Ghaoui, E. Feron, and V. Balakrishnan, Linear Matrix
Inequalities in System and Control Theory, SIAM.
- L. El Ghaoui, and S.-I. Niculescu, Advances in Linear Matrix
Inequality Methods in Control, SIAM.
SoftwareSome tools are:
Hansson, Department of Electrical Engineering (email@example.com, phone: +46 13
ExamFrom 2016-06-?? until 2016-08-31 you may down-load the exam.
After 36 hours you put the exam in an envelop, seal it, and hand it in.
Exams should be handed in no later than 2016-08-31. Go