course-details-portlet

TTK4135

Optimization and Control

Credits 7.5
Level Third-year courses, level III
Course start Spring 2022
Duration 1 semester
Language of instruction English and norwegian
Location Trondheim
Examination arrangement Portfolio assessment

About

About the course

Course content

The course treats optimization. The candidates learn to formulate optimization problems and solve these through appropriate algorithms and software. Optimality conditions like the Karush-Kuhn-Tucker (KKT) conditions are discussed and conditions for global and local conditions are analyzed. Key optimization classes of problems including linear programming (LP), quadratic programming (QP) and nonlinear programming (NP) are studied and applied in different settings.

The course includes advanced control of dynamic systems with emphasis on Model Predictive Control (MPC).

Learning outcome

Knowledge:

- Ability to formulate appropriate engineering problems as a mathematical optimization problem.

- Knowledge of typical engineering problems which are suitable for optimization.

- Ability to analyze and solve an optimization problem; in particular linear programs (LP), quadratic programs (QP) and nonlinear programs (NP).

- Ability to analyze and design optimal controllers; in particular Model Predictive Controllers (MPC).

- Knowledge of optimization software.

 

Skills:

- Solve suitable optimization problems using Matlab.

- Use optimization in controllers; in particular Model Predictive Control (MPC).

- Complete a small optimization project.

- Analyze a problem and contribute to innovative design solutions.

 

General competence:

- Communicate technical issues with specialists in cross-disciplinary teams and the general public.

- Conscious attitude towards the use of optimization within engineering.

Learning methods and activities

The course is given as a mixture of lectures, assignments and a laboratory project. Seven of the assignments and the laboratory report must be approved to enter the final exam.

Compulsory assignments

  • Exercises

Further on evaluation

Portfolio evaluation is used the final grade in the subject. Parts of the portfolio are the final exam in writing 80%, and a project report 20%. The result of each part is given in percentage units, while evaluation of the entire portfolio (the final grade) is given as a letter. To pass the course, all parts of the exam must be evaluated and given a passed grade level.

If there is a re-sit examination, the examination form may change from written to oral.

Both project report (20%) need to be retaken in addition to the main exam (80%).

Course materials

Information on this is given at the start of the semester.

Credit reductions

Course code Reduction From
SIE3030 7.5 sp
This course has academic overlap with the course in the table above. If you take overlapping courses, you will receive a credit reduction in the course where you have the lowest grade. If the grades are the same, the reduction will be applied to the course completed most recently.

Subject areas

  • Technological subjects

Contact information

Course coordinator

Department with academic responsibility

Department of Engineering Cybernetics

Examination

Examination

Examination arrangement: Portfolio assessment
Grade: Letter grades

Ordinary examination - Spring 2022

Work
Weighting 40/100
Home exam (1)
Weighting 60/100 Date Release 2022-05-13
Submission 2022-05-13 Time Release 09:00
Submission 13:00 Duration 4 hours Exam system Inspera Assessment
  • Other comments
  • 1) Merk at eksamensform er endret som et smittevernstiltak i den pågående koronasituasjonen.

Re-sit examination - Summer 2022

Work
Weighting 40/100
Home exam
Weighting 60/100 Duration 4 hours Exam system Inspera Assessment

All about examinations at NTNU