Omfattning: 5
Tidtabel: 08.01.2019 - 18.02.2019
Ansvarslärare (är i kraft 01.08.2018-31.07.2020):
Sirkka-Liisa Jämsä-Jounela
Undervisningsperiod (är i kraft 01.08.2018-31.07.2020):
III
Lärandemål (är i kraft 01.08.2018-31.07.2020):
After completing the course, the student*Understands the main principles of the model identification
*Is familiar with the identification toolbox
*Understands and is able to apply Kalman filtering for the state estimation
*Is familiar with the basics of multivariable control
*Knows the discrete time control and is able to formulate and solve dynamic models in discrete time
*Understands and is able to use Model Predictive Control (MPC)
Innehåll (är i kraft 01.08.2018-31.07.2020):
The course includes the selected topics of advanced control theory: model identification, state estimation with Kalman filter, multivariable control, discrete time systems and design of digital controllers, model predictive control. The course is focused on multivariate systems.
Assignments:
Identification of the mixing tank
PI controller and decouplers design for the 3-tank system
MPC design + state estimation for the three-tank system
Homeworks:
Experimental modelling of a distillation column
Estimation using a Kalman filter
Metoder, arbetssätt och bedömningsgrunder (är i kraft 01.08.2018-31.07.2020):
Lectures
Exercises
Assignments
Independent study and exam
Arbetsmängd (är i kraft 01.08.2018-31.07.2020):
Lectures 24 h
Exercises 24 h
Assignments + independent study 83 h
Exam 4 h
Studiematerial (är i kraft 01.08.2018-31.07.2020):
To be announced later.
Ersättande prestationer (är i kraft 01.08.2018-31.07.2020):
KE-90.4510 Control Applications in Process Industries (6 op), CHEM-E7145 Advanced Process Control Methods and Process Control Project Work (5 cr)
Bedömningsskala (är i kraft 01.08.2018-31.07.2020):
Fail, 1 - 5
Anmälning (är i kraft 01.08.2018-31.07.2020):
WebOodi