Type of course

Admission requirements

Bachelor degree in Engineering. Required prerequisites: FYS-2006 Signal Processing and AUT-2005 Reguleringsteknikk or equivalent courses. Recommended prerequisites: STA-2001 Stochastic processes. 

MATLAB

Obligatory prerequisites

Course content

Kalman filtering: 

• Statistical background 
• Mathematical model 
• Application areas 

Multivariable control 

Numerical optimization 

Optimal control: 

• Model Predictive Control (MPC) 
• Linear-quadratic regulator (LQR) 

Recommended prerequisites

Objectives of the course

Knowledge

• Ability to design an appropriate Kalman filter for state estimation.
• Ability to identify multivariable control problems.
• Ability to formulate appropriate engineering problems as a mathematical optimization problem.
• Ability to analyze and solve an optimization problem; in particular linear programs (LP), quadratic problems (QP) and nonlinear programs (NP).
• Ability to analyze and design optimal controllers; in particular model predictive controllers (MPC).

Professional skills

• Solve suitable optimization problems using Matlab.
• Use Kalman filter and optimization in controllers.

General competence

• Understand relevant definitions and terms.
• Communicate with others in the field.
• Conscious attitude towards the use of optimization within engineering.

Language of instruction and examination

Teaching methods

Assessment

5-7 approved assignments and mandatory project with report.

Project with report (50%) and oral exam (50%). Letter grading A - F.

Recommended reading/syllabus