Course syllabus adopted 2021-02-26 by Head of Programme (or corresponding).
Overview
- Swedish nameDesign av linjära reglersystem
- CodeSSY285
- Credits7.5 Credits
- OwnerMPSYS
- Education cycleSecond-cycle
- Main field of studyAutomation and Mechatronics Engineering, Electrical Engineering, Chemical Engineering with Engineering Physics, Engineering Physics
- DepartmentELECTRICAL ENGINEERING
- GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Course round 1
- Teaching language English
- Application code 35124
- Maximum participants180
- Block schedule
- Open for exchange studentsNo
Credit distribution
Module | Sp1 | Sp2 | Sp3 | Sp4 | Summer | Not Sp | Examination dates |
|---|---|---|---|---|---|---|---|
| 0111 Design exercise + laboratory 3 c Grading: UG | 3 c | ||||||
| 0211 Examination 4.5 c Grading: TH | 4.5 c |
|
In programmes
- MPAUT - AUTOMOTIVE ENGINEERING, MSC PROGR, Year 2 (elective)
- MPBME - BIOMEDICAL ENGINEERING, MSC PROGR, Year 2 (elective)
- MPEPO - SUSTAINABLE ELECTRIC POWER ENGINEERING AND ELECTROMOBILITY, MSC PROGR, Year 1 (elective)
- MPEPO - SUSTAINABLE ELECTRIC POWER ENGINEERING AND ELECTROMOBILITY, MSC PROGR, Year 2 (elective)
- MPISC - INNOVATIVE AND SUSTAINABLE CHEMICAL ENGINEERING, MSC PROGR, Year 1 (compulsory elective)
- MPISC - INNOVATIVE AND SUSTAINABLE CHEMICAL ENGINEERING, MSC PROGR, Year 2 (elective)
- MPMOB - MOBILITY ENGINEERING, MSC PROGR, Year 1 (elective)
- MPSYS - SYSTEMS, CONTROL AND MECHATRONICS, MSC PROGR, Year 1 (compulsory)
Examiner
Torsten Wik- Head of Unit, Systems and Control, Electrical Engineering
Eligibility
General entry requirements for Master's level (second cycle)Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.
Specific entry requirements
English 6 (or by other approved means with the equivalent proficiency level)Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.
Course specific prerequisites
A basic course in automatic control including some familiarity with state space models.Aim
The purpose of this course is to introduce and investigate techniques to analyze and design model based control systems. Linear state space modeling framework is applied to create a basis for different type of controller and state estimation methods. Starting from a pure state-feedback concept down to the optimal control methods, a large variety of feedback control techniques are presented with special attention on applications. Kalman filtering as an optimal way of state reconstruction is discussed in details. In this course, systems with multiple input and outputs are also analyzed from input-output point of view, through transfer function matrices. Disturbances, modeling uncertainties and robustness are also highlighted in the course. Exercises are playing an important role along the entire course.Learning outcomes (after completion of the course the student should be able to)
- Design control algorithms for linear time-invariant (LTI) dynamical systems with some state-space methods presented.
- Become familiar with the concept of the state-space terminology.
- Linearize nonlinear continuous time multivariable models (MIMO). Have some knowledge on deriving discrete time forms from continuous time LTI descriptions by a suitable sampling.
- Understand model descriptions for linear time-invariant multivariable systems. Analyze these type of systems from the point of view controllability, observability and stability.
- Explain and design discrete time multivariable state feedback controllers, based on linear quadratic optimization.
- Explain, design, and analyze Kalman filters, and apply them for state estimation combined with controller design, i.e. LQG-control. Understand the principle of separation, analyze closed-loop optimal behavior.
- Become familiar with the the basics of MIMO transfer functions and with their most important analytical properties. Understand concept for frequency domain analysis and synthesis of MIMO systems.
- Define stability of dynamic systems under the presence of additive and multiplicative uncertainties. Provide with robustness uncertainty tests. Understand and design robust control techniques. Understand basic concept of decentralized and distributed control algorithms.
Content
- Multivariable systems. MIMO (Multiple input-multiple output) vs. SISO (single input-single output) dynamical systems. Nonlinear dynamical systems and linearization. Basic control concepts (feedback, stability).
- State-space realizations, state transformation. Continuous and discrete time descriptions. Discretization technique. Analytic properties of linear dynamical systems. Controllability, observability, multivariable poles and zeros, stability.
- Analytic properties of linear dynamical systems. Controllability, observability, multivariable poles and zeros, stability.
- Closed-loop control systems in state-space. Linear quadratic regulation
- State observer design. Kalman filtering. Separation principle. Linear quadratic gaussian control (LQG).
- Transfer function matrices. Sensitivity, robustness. Performance limitations in controlled systems.
- Uncertainty and robustness. Disturbance rejecting robust control and state estimator.
- Introduction to large-scale system design. Distributed and decentralized control. Decoupling.
Organisation
The course is divided into a series of lectures, problem solving, and a mandatory project including assignments and laboratory sessions.Literature
Control textbook and lecture slides.Examination including compulsory elements
Written exam with TH grading; project with assignments and laboratory sessions (pass/fail).The course examiner may assess individual students in other ways than what is stated above if there are special reasons for doing so, for example if a student has a decision from Chalmers on educational support due to disability.