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Modeling and 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
2012 (English)In: Structural and multidisciplinary optimization (Print), ISSN 1615-147X, E-ISSN 1615-1488, Vol. 45, no 2, 257-274 p.Article in journal (Refereed) Published
Abstract [en]

In this paper we describe the modeling and optimization of what we refer to as Neuro-Mechanical Shape Memory Devices (NMSMDs). These are active mechanical structures which are designed to take on specific shapes in response to certain external stimuli. An NMSMD is a particular example of a Neuro-Mechanical Network (NMN), a mechanical structure that consists of a network of simple but multifunctional elements. In the present work, each element contains an actuator and an artificial neuron, and when assembled into a structure the elements form an actuated truss with a superimposed recurrent neural network.

The task of designing an NMSMD is cast as an optimization problem in which a measure of the error between the actual and desired shape for a number of given stimuli is minimized. The optimization problems are solved using a gradient based solver, and some numerical examples are provided to illustrate the results from the design process and some aspects of the proposed model.

Place, publisher, year, edition, pages
Springer, 2012. Vol. 45, no 2, 257-274 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-67845DOI: 10.1007/s00158-011-0684-1ISI: 000298500500008OAI: oai:DiVA.org:liu-67845DiVA: diva2:413609
Note
Funding agencies|National Graduate School of Scientific computing (NGSSC)||Swedish Research Council| DNR 2006-6218 |Available from: 2011-04-29 Created: 2011-04-29 Last updated: 2017-12-11Bibliographically approved
In thesis
1. Optimal Design of Neuro-Mechanical Networks
Open this publication in new window or tab >>Optimal Design of Neuro-Mechanical Networks
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis concerns modeling and optimal design of Neuro-Mechanical Networks. A Neuro-Mechanical Network (NMN) can be described as an active mechanical structure, made up from a network of simple but multifunctional elements that interact with their nearest neighbors. The concept is of mechatronic character as it involves integration of actuators, sensors, signal processing, and control, into a mechanical structure.

The first part of the thesis consists of three chapters. The first of these chapters contains a brief introduction to the NMN-concept and the present work. In the second chapter, the particular type of NMNs considered here is described in more detail, and the third chapter constitute a brief survey of some works relevant to optimization of active structures, including enabling technologies and static and dynamic shape control.

The second part of the thesis consists of two papers, where the first paper describes optimal design of NMNs for static shape control, while the second paper is concerned with optimal design of structures that exhibit oscillatory motion.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2011. 38 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1495
Keyword
Neuro-mechanical networks, active structures, neural networks, structural optimization
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-67847 (URN)LIU-TEK-LIC-2011:34 (Local ID)978-91-7393-141-0 (ISBN)LIU-TEK-LIC-2011:34 (Archive number)LIU-TEK-LIC-2011:34 (OAI)
Presentation
2011-05-20, ACAS, Hus A, Campus Valla, Linköpings universitet, Linköping, 13:15 (Swedish)
Opponent
Supervisors
Available from: 2011-04-29 Created: 2011-04-29 Last updated: 2017-05-15Bibliographically approved
2. 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

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Thore, Carl-JohanKlarbring, Anders

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