SF2832 Mathematical Systems Theory 7.5 credits
Matematisk systemteori
Educational level
Second cycleAcademic level (A-D)
DSubject area
Mathematics
Grade scale
A, B, C, D, E, FX, F
Course offerings
Spring 13 for programme students
Periods
Spring 13 P3 (7.5 credits)
Application code
60192Start date
2013 week: 2End date
2013 week: 11Language of instruction
EnglishCampus
KTH CampusNumber of lectures
Number of exercises
Tutoring time
DaytimeForm of study
NormalNumber of places
No limitationSchedule
Schedule (new window)Course responsible
Xiaoming Hu <hu@kth.se>
Target group
Master students in Mathematics,
Master students in Aerospace Engineering,
Master students in Systems, Control and Robotics.
Part of programme
Autumn 13 for programme students
Periods
Autumn 13 P2 (7.5 credits)
Application code
50741Start date
2013 week: 45End date
2014 week: 3Language of instruction
EnglishCampus
KTH CampusNumber of lectures
Number of exercises
Tutoring time
DaytimeForm of study
NormalNumber of places *
10 - 60*) The Course date may be cancelled if number of admitted are less than minimum of places. If there are more applicants than number of places selection will be made.
Schedule
Schedule (new window)Course responsible
Xiaoming Hu <hu@kth.se>
Target group
Master students in Mathematics,
Master students in Applied and Computational Mathematics,
Master students in Aerospace Engineering,
Master students in Systems, Control and Robotics.
Part of programme
- Master (Two Years), Aerospace Engineering, year 1, SYS, Optional
- Master (Two Years), Aerospace Engineering, year 2, SYS, Optional
- Master (Two Years), Applied and Computational Mathematics, year 1, Conditionally Elective
- Master (Two Years), Applied and Computational Mathematics, year 1, OPSA, Conditionally Elective
- Master (Two Years), Mathematics, year 1, Optional
- Master (Two Years), Systems, Control and Robotics, year 1, Recommended
- Master (Two Years), Systems, Control and Robotics, year 2, Recommended
Learning outcomes
This is an introductory course in mathematical systems theory. The subject provides the mathematical foundation of modern control theory, with application in aeronautics, electrical networks, signal processing, and many other areas. The aim of the course is that you should acquire a systematic understanding of linear dynamical systems, which is the focus of this course. The acquirement of such knowledge is not only very useful preparation for work on system analysis and design problems that appear in many engineering fields, but is also necessary for further studies in control and signal processing.
The overall goal of the course is to provide an understanding of the basic ingredients of linear systems theory and how these are used in analysis and design of control, estimation and filtering systems. In the course we take the state-space approach, which is well suited for efficient control and estimation design.
Measurable goals:
To pass the course, the student should be able to do the following:
- Analyze the state-space model with respect to minimality, observability, reachability, detectability and stabilizability.
- Explain the relationship between input-output (external) models and state-space (internal) models for linear systems and derive such models from the basic principles.
- Derive a minimal state-space model using the Kalman decomposition.
- Use algebraic design methods for state feedback design with pole assignment, and construct stable state observers by pole assignment and analyze the properties of the closed loop system obtained when the observer and the state feedback are combined to an observer based controller.
- Apply linear quadratic techniques to derive optimal state feedback controllers.
- Design a Kalman filter for optimal state estimation of linear systems subject to stochastic disturbances.
- Solve the Riccati equations that appear in optimal control and estimation problems.
- Apply the methods given in the course to solve example problems (one should also be able to use the Control System Toolbox in Matlab to solve the linear algebra problems that appear in the examples).
To receive the highest grade, the student should in addition be able to do the following:
- Integrate the tools learnt during the course and apply them to more complex problems.
- Explain how the above results and methods relate and build on each other.
- Explain the mathematical (mainly linear algebra) foundations of the techniques used in linear systems theory and apply those techniques flexibly to variations of the problems studied in the course.
- Solve fairly simple but realistic control design problems using the methods in the course.
Course main content
Linear control systems: reachability, observability, stability, realization theory, minimality, feedback, pole-assignment, observers. Linear-quadratic optimal control, matrix Riccati equation and theory for the algebraic Riccati equation. Kalman filtering.
Eligibility
In general:
150 university credits (hp) including 28 hp in Mathematics and 6 hp in Mathematical Statistics. Documented proficiency in English corresponding to English B.
More precisely for KTH students:
Passed courses in calculus, linear algebra, differential equations, mathematical statistics, numerical analysis. A passed course in control theory is an advantage.
Prerequisites
The prerequisites is a Swedish or foreign degree equivalent to Bachelor of Science of 180 ECTS credits, with at least 45 ECTS credits in mathematics. The students should have documented knowledge corresponding to basic university courses in analysis, linear algebra, numerical analysis, differential equations and transforms, mathematical statistics, and optimization.
Literature
Lindquist & Sand: An introduction to mathematical systems theory (Lecture notes)
Examination
- HEM1 - Assignments, , grade scale: P, F
- TEN1 - Examination, 7.5 credits, grade scale: A, B, C, D, E, FX, F
Requirements for final grade
A written examination (TEN1; 7,5 hp).
Optional homework sets that give bonus credit on the exam.
Offered by
SCI/Mathematics
Examiner
Add-on studies
SF2852 Geometric control theory.
Version
Course plan valid from:
Spring 11.
Examination information valid from:
Autumn 07.
