TTK4115 - Linear System Theory

About

Examination arrangement

Examination arrangement: Portfolio assessment
Grade: Letters

Evaluation form Weighting Duration Examination aids Grade deviation
Work 50/100
Written examination 50/100 4 hours D

Course content

Theory for linear multivariable systems, state space models, discretization, canonical forms and realizations, Lyapunov stability, controllability and observability, state feedback, LQ control, state estimation, the Kalman filter, descriptions of stochastic processes and random signals.

Learning outcome

Knowledge:
Detailed knowledge about state space representation of linear time invariant systems in continuous and discrete time. Knowledge about representation and characterization of random signals in linear systems. Detailed knowledge about fundamental concepts like controlability, observability, and stability for linear multivariable systems. Substantial knowedge about methods for construction of multivariable controllers for linear systems, and algorithms and methods for state estimation and use of state estimation for feedback in linear control systems. Knowledge of linearization of nonlinear systems and use of extended Kalman filtering for state estimation in nonlinear systems.

Skills:
Being able to formulate specifications and dynamic models as a basis for design of linear control systems and state estimators under influence of noise and disturbances. Being able to transform models between continuous and discrete time, and between state space and transfer function matrix representations. Being able to design and tune parameters of controllers with LQ and pole placement. Being able to design and tune parameters of observers and Kalman filters. Being able to apply linear algebra and Matlab for analysis and design of linear control systems. Being able to apply Simulink for rapid prototyping and experimental testing of control systems.

General competence:
Understand strengths and limitations of theoretical analysis versus experimental testing. Good system understanding, i.e. how sub-systems consisting of hardware, software, physical systems and humans interact. Have a solid basis for advanced studies in control engineering.

Learning methods and activities

Lectures, two compulsory projects, compulsory assignments.

Compulsory assignments

  • Exercises

Further on evaluation

Portfolio evaluation is the basis for the final grade in the subject. Parts of the portfolio are final exam in writing 50% and project assignments 50%. The result for each part is given in percentage units, while evaluation of the entire portfolio (the final grade) is given as a letter.
If there is a re-sit examination, the examination form may change from written to oral.
In the case that the student receives an F/Fail as a final grade after both ordinary and re-sit exam, then the student must retake the course in its entirety. Submitted work that counts towards the final grade will also have to be retaken

Specific conditions

Exam registration requires that class registration is approved in the same semester. Compulsory activities from previous semester may be approved by the department.

Course materials

Information will be given when the course starts.

Credit reductions

Course code Reduction From To
SIE3015 7.5

Timetable

Detailed timetable

Examination

Examination arrangement: Portfolio assessment

Term Statuskode Evaluation form Weighting Examination aids Date Time Room *
Autumn ORD Written examination 50/100 D 2017-12-09 09:00 R D1-185 Datasal , KJL1 , E1 , E2 , E3 , R73
Autumn ORD Work 50/100
  • * The location (room) for a written examination is published 3 days before examination date.
If more than one room is listed, you will find your room at Studentweb.