liu.seSearch for publications in DiVA
Change search
Refine search result
1 - 6 of 6
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Gunnarsson, Svante
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Recursive Identification of Physical Parameters in a Flexible Robot Arm2004In: Asian journal of control, ISSN 1561-8625, E-ISSN 1561-8625, Vol. 6, p. 407-414Article in journal (Refereed)
    Abstract [en]

    Recursive identification of a physically parameterized model of a single link flexible robot arm is considered. The parameters are estimated using a recursive prediction error method applied to a linear continuous time model structure and discrete time data. The algorithm is applied to real data from an industrial robot, and three important parameters are identified using only measurements of the motor angle. The experiments show that the particular parameter that is estimated will have big influence on the algorithm behavior.

  • 2.
    Leissner, Patrik
    et al.
    Autoliv, Linkoping, Sweden.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering. ABB Robot, Sweden.
    Some Controllability Aspects for Iterative Learning Control2019In: Asian journal of control, ISSN 1561-8625, E-ISSN 1561-8625, Vol. 21, no 3, p. 1057-1063Article in journal (Refereed)
    Abstract [en]

    Some controllability aspects for iterative learning control (ILC) are discussed. Via a batch (lifted) description of the problem a state space model of the system to be controlled is formulated in the iteration domain. This model provides insight and enables analysis of the conditions for and relationships between controllability, output controllability and target path controllability. In addition, the property miminum lead target path controllability is introduced. This property, which is connected to the number of time delays, plays an important role in the design of ILC algorithms. The properties are illustrated by a numerical example.

  • 3.
    Ng, Kok Yew
    et al.
    Monash University, Australia.
    Tan, Chee Pin
    Monash University, Australia.
    Akmeliawati, Rini
    International Islamic University, Kuala Lumpur, Malaysia.
    Edwards, Christopher
    Leicester University, UK.
    Disturbance decoupled fault reconstruction using sliding mode observers2010In: Asian journal of control, ISSN 1561-8625, E-ISSN 1561-8625, Vol. 12, no 5, p. 656-660Article in journal (Refereed)
    Abstract [en]

    This paper investigates and presents conditions that guarantee disturbance decoupled fault reconstruction using sliding mode observers, which are less stringent than those of previous work, and show that disturbance reconstruction is not necessary. An aircraft model validates the ideas proposed in this paper.

  • 4.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Disturbance Rejection using an ILC Algorithm with Iteration Varying Filters2004In: Asian journal of control, ISSN 1561-8625, E-ISSN 1561-8625, Vol. 6, no 3, p. 432-438Article in journal (Refereed)
    Abstract [en]

    An Iterative Learning Control disturbance rejection approach is considered and it is shown that iteration variant learning filters can asymptotically give the controlled variable zero error and zero variance. Convergence is achieved with the assumption that the relative model error is less than one. The transient response of the suggested ILC algorithm is also discussed using a simulation example.

  • 5.
    Ooi, Jeremy Hor Teong
    et al.
    Monash University Malaysia.
    Ng, Kok Yew
    Monash University Malaysia.
    Tan, Chee Pin
    Monash University Malaysia.
    State and Fault Estimation For Infinitely Unobservable Descriptor Systems Using Sliding Mode Observers2014In: Asian journal of control, ISSN 1561-8625, E-ISSN 1561-8625Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel scheme for estimating states and faults for a class of infinitely unobservable descriptor systems using sliding mode observers (SMOs). Treating certain states of the original infinitely unobservable system as unknown inputs results in a reduced-order system that is infinitely observable. Then by designing the SMO based on the reduced-order system, state estimation and fault reconstruction is achieved, thus relaxing the infinite observability requirement of the original system. The necessary and sufficient conditions in terms of the original system matrices are also investigated. A simulation example verifies the claims made in this paper.

  • 6.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Framework for Analysis of Observer-Based ILC2011In: Asian journal of control, ISSN 1561-8625, E-ISSN 1561-8625, Vol. 13, no 1, p. 3-14Article in journal (Refereed)
    Abstract [en]

    A framework for iterative learning control (ILC) is proposed for the situation when an ILC algorithm uses an estimate of the controlled variable obtained from an observer-based estimation procedure. Assuming that the ILC input converges to a bounded signal, a general expression for the asymptotic error of the controlled variable is given. The asymptotic error is exemplified by an ILC algorithm applied to a flexible two-mass model of a robot joint.

1 - 6 of 6
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf