- Introduction to model predictive control (concept, variants, applications, research)
- Fundamentals of discrete-time systems (structures, discretization, stability, state feedback control, controllability, state observation, observability, separation principle, reference tracking, integral control, disturbance rejection, disturbance estimation, illustration for an active suspension system)
- Fundamentals of optimization (nonlinear optimization, convex optimization, optimality conditions, linear programming, quadratic programming)
- Model predictive control without constraints (formulation and solution of the optimization problem for a finite horizon (system model, cost function, analytical solution), application of the solution for a receding horizon, formulation and solution of the optimization problem for an infinite horizon (LQR), comparison)
- Model predictive control with constraints (Types and handling of constraints, formulation and solution of the optimization problem for a finite horizon (constraint models, numerical solution), application of the solution for a receding horizon, extensions like warm starting, multiple horizons, scaling, linear cost and soft constraints)
- Stability and feasibility (stability of model predictive control without constraints, feasibility and stability of model predictive control with constraints)
- Reference tracking and disturbance rejection (reference tracking based on target calculation and the delta input formulation, disturbance rejection based on disturbance estimation, preview control)
- Robust model predictive control (polytopic and norm-bounded uncertainties, linear matrix inequalities, parameter-dependent Lyapunov functions, robust stability and control)
- Illustration of the contents using simulations in MATLAB/Simulink
Module EIT-JEM-515-M-7
Model Predictive Control (M, 4.0 LP)
Module Identification
Module Number | Module Name | CP (Effort) |
---|---|---|
EIT-JEM-515-M-7 | Model Predictive Control | 4.0 CP (120 h) |
Basedata
CP, Effort | 4.0 CP = 120 h |
---|---|
Position of the semester | 1 Sem. in WiSe |
Level | [7] Master (Advanced) |
Language | [EN] English |
Module Manager | |
Lecturers | |
Area of study | [EIT-JEM] Electro Mobility |
Reference course of study | [EIT-88.?-SG#2021] M.Sc. Automation and Control (A&C) [2021] |
Livecycle-State | [NORM] Active |
Courses
Type/SWS | Course Number | Title | Choice in Module-Part | Presence-Time / Self-Study | SL | SL is required for exa. | PL | CP | Sem. | |
---|---|---|---|---|---|---|---|---|---|---|
2V+1U | EIT-JEM-515-K-7 | Model Predictive Control
| P | 42 h | 78 h | - | - | PL1 | 4.0 | WiSe |
- About [EIT-JEM-515-K-7]: Title: "Model Predictive Control"; Presence-Time: 42 h; Self-Study: 78 h
Examination achievement PL1
- Form of examination: written exam (Klausur) (90 Min.)
- Examination Frequency: each semester
Evaluation of grades
The grade of the module examination is also the module grade.
Contents
Competencies / intended learning achievements
After completing this module you can...
- ... describe the variants and applications of model predictive control.
- ... explain the theoretical background of model predictive control (optimization, stability, feasibility, robustness, reference tracking, disturbance rejection).
- ... analyze the stability and feasibility of model predictive controllers.
- ... design, implement and evaluate model predictive controllers using MATLAB/Simulink.
Requirements for attendance (informal)
Modules:
Requirements for attendance (formal)
None
References to Module / Module Number [EIT-JEM-515-M-7]
Course of Study | Section | Choice/Obligation |
---|---|---|
[EIT-88.781-SG#2010] M.Sc. Electrical and Computer Engineering [2010] | Elective Subjects | [W] Elective Module |
[EIT-88.?-SG#2021] M.Sc. Electrical and Computer Engineering [2021] | Technical Elective Modules | [W] Elective Module |
[EIT-88.A20-SG#2021] M.Sc. European Master in Embedded Computing Systems (EMECS) [2021] | Elective Subjects | [W] Elective Module |
[EIT-88.?-SG#2021] M.Sc. Automation and Control (A&C) [2021] | Major "Connected Automation Systems" (CAS) | [P] Compulsory |
[EIT-88.?-SG#2021] M.Sc. Embedded Computing Systems (ESY) [2021] | Elective Subjects | [W] Elective Module |