Optimal Design of Neuro-Mechanical Oscillators with Stability Constraints
2015 (English)In: ZAMM-ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK, ISSN 0044-2267, Vol. 95, no 6, 620-637 p.Article in journal (Refereed) Published
This paper concerns optimal design of so-called Neuro-Mechanical Oscillators (NMOs). An NMO is a new type of bio-inspired mechatronic system which consists of an actuated truss with a recurrent neural network (RNN) superimposed onto it. By choosing the entries of the weight matrix of the RNN, an NMO can be designed, using numerical optimization, to generate pre-specified time-varying motions when subject to certain time-varying input signals. However, to rule out possible dependence of the motion on the initial state of the system as well as convergence into limit cycles, some form of constraints must be imposed on the system's design parameters. To derive such constraints, we investigate under what conditions the influence of the initial state eventually vanishes and the motion becomes completely determined by the input signal. Three sufficient criteria are presented for RNNs, but the possibility of large mechanical deformations most likely rule out global system level results. For sufficiently small deformations, however, local results are obtained, and a numerical example provided in the paper indicates that these can be useful for designing practical systems.
Place, publisher, year, edition, pages
Wiley-VCH Verlagsgesellschaft, 2015. Vol. 95, no 6, 620-637 p.
Neuro-Mechanical Oscillators; recurrent neural networks; optimal design; convergent systems
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-76981DOI: 10.1002/zamm.201300031ISI: 000355725900004OAI: oai:DiVA.org:liu-76981DiVA: diva2:524021