liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Some Aspects of Optimal Design of Neuro-Mechanical Shape Memory Devices
Linköping University, Department of Management and Engineering, Mechanics. Linköping University, The Institute of Technology.
Linköping University, Department of Management and Engineering, Mechanics. Linköping University, The Institute of Technology.ORCID iD: 0000-0001-8460-0131
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Neuro-Mechanical Shape Memory Devices (NMSMDs) are a new type of active mechanical systems designed to take on prescribed shapes when subjected to a certain input stimuli. In an earlier paper we derived a mathematical model for NMSMDs and posed an optimization problem for finding system parameters that would result in an NMSMD with a certain desired behavior. The optimization problem was highly nonlinear and non-convex, making it difficult to find good solutions. In this paper, through using a numerical example, we show that these difficulties can be alleviated by a new formulation of the original optimization problem. However, it is also shown that, due to the possible existence of multiple equilibrium points for the governing equations of NMSMDs, solutions to the new optimization problem must be carefully validated.

National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-76982OAI: oai:DiVA.org:liu-76982DiVA: diva2:524023
Available from: 2012-04-27 Created: 2012-04-27 Last updated: 2017-05-15Bibliographically approved
In thesis
1. Optimal Design of Neuro-Mechanical Networks
Open this publication in new window or tab >>Optimal Design of Neuro-Mechanical Networks
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Many biological and artificial systems are made up from similar, relatively simple elements that interact directly with their nearest neighbors. Despite the simplicity of the individual building blocks, systems of this type, network systems, often display complex behavior — an observation which has inspired disciplines such as artificial neural networks and modular robotics. Network systems have several attractive properties, including distributed functionality, which enables robustness, and the possibility to use the same elements in different configurations. The uniformity of the elements should also facilitate development of efficient methods for system design, or even self-reconfiguration. These properties make it interesting to investigate the idea of constructing mechatronic systems based on networks of simple elements.

This thesis concerns modeling and optimal design of a class of active mechanical network systems referred to as Neuro-Mechanical Networks (NMNs). To make matters concrete, a mathematical model that describes an actuated truss with an artificial recurrent neural network superimposed onto it is developed and used. A typical NMN is likely to consist of a substantial number of elements, making design of NMNs for various tasks a complex undertaking. For this reason, the use of numerical optimization methods in the design process is advocated. Application of such methods is exemplified in four appended papers that describe optimal design of NMNs which should take on static configurations or follow time-varying trajectories given certain input stimuli. The considered optimization problems are nonlinear, non-convex, and potentially large-scale, but numerical results indicate that useful designs can be obtained in practice.

The last paper in the thesis deals with a solution method for optimization problems with matrix inequality constraints. The method described was developed primarily for solving optimization problems stated in some of the other appended papers, but is also applicable to other problems in control theory and structural optimization.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2012. 42 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1444
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-76984 (URN)978-91-7519-900-9 (ISBN)
Public defence
2012-06-01, C3, C-huset, Campus Valla, Linköpings universitet, Linköping, 11:15 (English)
Opponent
Supervisors
Available from: 2012-04-27 Created: 2012-04-27 Last updated: 2017-05-15Bibliographically approved

Open Access in DiVA

No full text

Authority records BETA

Thore, Carl-JohanKlarbring, Anders

Search in DiVA

By author/editor
Thore, Carl-JohanKlarbring, Anders
By organisation
MechanicsThe Institute of Technology
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 22 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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