Linear and Neuro Control Strategies; Some Experimental Results
(2000) In MSc ThesesDepartment of Automatic Control
- Abstract
- The variety of different controllers is today very big. Much research is done in the field of neural network control and more well established technologies are sometimes looked at as old fashioned. The work is much based on the identification of a process model. In this report some different controllers have been built to see if neural networks are a good alternative to classic controllers. The classical controllers are a pure linear controller and an adaptive linear controller
working with updating by a covariance matrix. The neural network controller is based on a process model made by a recurrent neural network. This model is used in an input-output feedback linearisation controller.
The identification with the neural network model is... (More) - The variety of different controllers is today very big. Much research is done in the field of neural network control and more well established technologies are sometimes looked at as old fashioned. The work is much based on the identification of a process model. In this report some different controllers have been built to see if neural networks are a good alternative to classic controllers. The classical controllers are a pure linear controller and an adaptive linear controller
working with updating by a covariance matrix. The neural network controller is based on a process model made by a recurrent neural network. This model is used in an input-output feedback linearisation controller.
The identification with the neural network model is very difficult to make. As often in the world of control the theory by far exceeds reality. It is possible to build good neural network controllers but they are today more another way of achieving the same thing as the conventional controllers. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8848343
- author
- Olsson, Henrik
- supervisor
- organization
- year
- 2000
- type
- H3 - Professional qualifications (4 Years - )
- subject
- publication/series
- MSc Theses
- report number
- TFRT-5643
- ISSN
- 0280-5316
- language
- English
- id
- 8848343
- date added to LUP
- 2016-03-20 18:15:11
- date last changed
- 2016-03-20 18:15:11
@misc{8848343, abstract = {{The variety of different controllers is today very big. Much research is done in the field of neural network control and more well established technologies are sometimes looked at as old fashioned. The work is much based on the identification of a process model. In this report some different controllers have been built to see if neural networks are a good alternative to classic controllers. The classical controllers are a pure linear controller and an adaptive linear controller working with updating by a covariance matrix. The neural network controller is based on a process model made by a recurrent neural network. This model is used in an input-output feedback linearisation controller. The identification with the neural network model is very difficult to make. As often in the world of control the theory by far exceeds reality. It is possible to build good neural network controllers but they are today more another way of achieving the same thing as the conventional controllers.}}, author = {{Olsson, Henrik}}, issn = {{0280-5316}}, language = {{eng}}, note = {{Student Paper}}, series = {{MSc Theses}}, title = {{Linear and Neuro Control Strategies; Some Experimental Results}}, year = {{2000}}, }