Course - Optimization and Control - TTK4135
TTK4135 - Optimization and Control
About
Examination arrangement
Examination arrangement: Aggregate score
Grade: Letter grades
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| Programming assignments | 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
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, programming assessments and a laboratory project. Seven of the assignments and the laboratory report must be approved to enter the final exam.
Compulsory assignments
- Exercises
- Laboratory report
Further on evaluation
There are two partial assessments in the course. The first is based on completion of programming assignments, and counts 20%. The second is the final (written) exam, which counts 80%.
If there is a re-sit examination, the examination form may change from written to oral.
When a non-passed course is re-taken, both partial assessments must be done again.
Specific conditions
Compulsory activities from previous semester may be approved by the department.
Recommended previous knowledge
Calculus 1, 2, 3 and 4 (TMA4100, TMA4105, TMA4115, TMA4120), TTK4105 Control Systems, TTK4115 Linear System Theory or a comparable background.
Course materials
Information on this is given at the start of the semester.
Credit reductions
| Course code | Reduction | From | To |
|---|---|---|---|
| SIE3030 | 7.5 |
No
Version: 1
Credits:
7.5 SP
Study level: Third-year courses, level III
Term no.: 1
Teaching semester: SPRING 2023
Language of instruction: English, Norwegian
Location: Trondheim
- Technological subjects
Department with academic responsibility
Department of Engineering Cybernetics
Examination
Examination arrangement: Aggregate score
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Spring ORD School exam 80/100 D 2023-06-08 09:00 PAPIR
-
Room Building Number of candidates - Spring ORD Programming assignments 20/100
-
Room Building Number of candidates - Summer UTS School exam 80/100 D
-
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"