Digital Control Engineering (121077)

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Dit vak is niet compleet. Als je over extra informatie beschikt, voeg deze alsjeblieft toe.

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Vakcode: {{{vakcode}}}
Materiaal: - College sheets mainly,

- The reader 'Digital Control Engineering' nr. 207 can be used as reference, but doesn't include all the material

Docenten: Prof. Dr. Ir. S. Stramigioli, Raffaella Carloni



Effectively the material for this course are the lecture sheets. To provide a more clear view of the context and to make it more easy to learn, this wiki page is set up. If every one makes a summary of the sheets of one lecture combined with some exercises it should be possible for everyone to finish the course.

If you are busy making a summery put your name in the part of the lecture so everyone knows that lecture is taken care of. To collaborate you need to make an account. This you can do by clicking on 'aanmelden' on the right top of the page.

Lecture 1


  • Introduction to the course
  • Different types of stability
  • Liapanov method
  • Introduction to the application in Control Engineering

Introduction to MIMO systems

The course handles about controllable systems. An typical example of a dynamical system is displayed in below: Afbeelding:Dynsys_121077_sjors.png

The plant has an input u and an output y. In case of a linear system, the path from the u to the y can be modeled by the structure shown below:


In case of a single input, single output (SISO) system. The input and the output variables are scalars. In case of an multi input, multi output (MIMO) system these in- and outputs become vectors. This means that the B and C vectors become matrices. The D value which is a scalar in a SISO system becomes a matrix.

The convension for the dimension of the vextors:

  • dim(x) = n
  • dim(u) = r
  • dim(y) = m

Stability analysis of MIMO systems

In SISO systems a system is stable if the eigenvalues of a matrix are negative. This method does not hold for MIMO systems.

Under construction by Sjors Hettinga

Lecture 2


  • I/O Decoupling
  • Optimal State Feed-back
  • Controllability and Observability

For more information: Uitleg over de Hamiltonian

Lecture 3


  • State Variable Filters (SVFs)
  • Identity Observer
  • Disturbances

Lecture 4


  • Kalman Filtering

Lecture 5


  • Steady Solution of DARE
  • Kalman Filtering
    • Constant bias
    • Sinusoidal Disturbance
  • Complete design with 20-sim

Lecture 6


  • Introduction to Computer Controlled Systems
  • Analysis
    • Sampling
    • Reconstruction

Lecture 7


  • The star * operator
  • Review of the z-transform
  • Conversion from s to z domain
  • Stability of discrete time systems
  • Approximation of Continuous time design

Lecture 8


  • Controllability and Observability in discrete time
  • LQR for discrete time
  • Kalman filter for discrete time

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