TTK4135 - Optimization and Control


Examination arrangement

Examination arrangement: Portfolio assessment
Grade: Letters

Evaluation Weighting Duration Grade deviation Examination aids
Work 20/100
School exam 80/100 4 hours D

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


- 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.



- 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%).

Specific conditions

Compulsory activities from previous semester may be approved by the department.

Course materials

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

Credit reductions

Course code Reduction From To
SIE3030 7.5
More on the course



Version: 1
Credits:  7.5 SP
Study level: Third-year courses, level III


Term no.: 1
Teaching semester:  SPRING 2022

Language of instruction: English, Norwegian

Location: Trondheim

Subject area(s)
  • Technological subjects
Contact information
Course coordinator:

Department with academic responsibility
Department of Engineering Cybernetics


Examination arrangement: Portfolio assessment

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring ORD Work 20/100
Room Building Number of candidates
Spring ORD School exam 80/100 D 2022-05-13 09:00
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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