dc.contributor.author |
Spentzas, KN |
en |
dc.contributor.author |
Kanarachos, SA |
en |
dc.date.accessioned |
2014-03-01T02:42:03Z |
|
dc.date.available |
2014-03-01T02:42:03Z |
|
dc.date.issued |
2002 |
en |
dc.identifier.issn |
0954-4054 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/30748 |
|
dc.subject |
Neural networks |
en |
dc.subject |
Semistochastic optimization |
en |
dc.subject |
Vehicles' hybrid suspension |
en |
dc.subject |
Vehicles' suspension |
en |
dc.subject.classification |
Engineering, Manufacturing |
en |
dc.subject.classification |
Engineering, Mechanical |
en |
dc.subject.other |
Evolutionary algorithms |
en |
dc.subject.other |
Mathematical models |
en |
dc.subject.other |
Neural networks |
en |
dc.subject.other |
Nonlinear control systems |
en |
dc.subject.other |
Hybrid suspension systems |
en |
dc.subject.other |
Vehicle suspensions |
en |
dc.title |
A neural network approach to the design of a vehicle's non-linear hybrid suspension system |
en |
heal.type |
conferenceItem |
en |
heal.identifier.primary |
10.1243/0954405021520364 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1243/0954405021520364 |
en |
heal.language |
English |
en |
heal.publicationDate |
2002 |
en |
heal.abstract |
In the following, a design method is presented for non-linear hybrid suspension systems of vehicles based on neural networks. A hybrid suspension system is one that behaves as an active suspension system only when the road excitation amplitude is above a prescribed value. Discontinuous operation of the controller helps to minimize the energy consumed by the actuator. The design targets of our method are the minimization of the vertical acceleration imposed on the passengers as well as the respect of all the design and construction constraints. The neural network used is obtained by a Taylor approximation of the unknown non-linear control function. Because of the existence of numerous local minima of the neural network, an evolutionary algorithm is used to solve the resulting neural network problem. |
en |
heal.publisher |
PROFESSIONAL ENGINEERING PUBLISHING LTD |
en |
heal.journalName |
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture |
en |
dc.identifier.doi |
10.1243/0954405021520364 |
en |
dc.identifier.isi |
ISI:000176337500018 |
en |
dc.identifier.volume |
216 |
en |
dc.identifier.issue |
5 |
en |
dc.identifier.spage |
833 |
en |
dc.identifier.epage |
838 |
en |