dc.creatorFerreira E.P.
dc.creatorMiranda V.M.
dc.date2011
dc.date2015-06-30T20:23:16Z
dc.date2015-11-26T14:48:48Z
dc.date2015-06-30T20:23:16Z
dc.date2015-11-26T14:48:48Z
dc.date.accessioned2018-03-28T21:59:39Z
dc.date.available2018-03-28T21:59:39Z
dc.identifier9781457714757
dc.identifierIeee International Conference On Control And Automation, Icca. , v. , n. , p. 991 - 996, 2011.
dc.identifier19483449
dc.identifier10.1109/ICCA.2011.6138050
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84858963937&partnerID=40&md5=58fc4c1bfe5aba1c01a1f51670661f58
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/107751
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/107751
dc.identifier2-s2.0-84858963937
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1253713
dc.descriptionThis article comprises a practical and original application of full neural predictors with fixed prediction horizon in backward movements of a Truck-Trailer-Trailer prototype of a multi-articulated mobile robot (MAMR), in the configuration space. It's used a new proposal based on static multilayer feedforward networks. This kind of predictor is useful for assisted operations or can be used as cores in simulators to analyze navigation strategies and for controller's synthesis and validation. The systematic and the presented tools are general. The training data set is composed by real data acquired from measurements of the prototype and by data generated from singular condition models. The article uses original models for the singularities and for the critical angles. These models were deduced from general movement equations of a MAMR with on-axle or off-axle hitching and with front or rear traction on the truck. The use of models for singularities is necessary because the circular conditions are situations of unstable equilibrium, which makes impossible to obtain enough data from open loop real systems. The model for critical angles is used to define the range for data acquisition before the jackknife. A MAMR's prototype is used for data acquisition and for synthesis and validation of neural networks. The characteristics of this robot are also presented. It is shown the results of the procedures applied to the collected data and to predictors with different prediction horizons during their training and validation, using the created Interface. The results demonstrate the good performance of the systematic and tools. © 2011 IEEE.
dc.description
dc.description
dc.description991
dc.description996
dc.descriptionDemcenko, A., Tamosiunaite, M., Vidugiriene, A., Saudargiene, A., Vehicle's steering signal predictions using neural networks (2008) IEEE Intelligent Vehicles Symposium
dc.descriptionFerreira, E.P., Lamego, M.M., Widrow, B., Neurointerfaces for semi-autonomous object moving systems (1999) Proceedings of the 14th World IFAC Congress., pp. 155-160. , Beijing, China
dc.descriptionFerreira, E.P., Kulitz, H., Silva, E.B., Pinheiro, M., Modeling and simulating backward of multiarticulated mobile robots or vehicles (2002) Fifth World Congress on Computational Mechanics, , Viena-Austria
dc.descriptionFerreira, E.P., Kulitz, H.R., Silva, E.B., Pinheiro, M., Modelling and simulating movements of multi-articulated mobile robots or vehicles-analytical and fuzzy approach (2004) Chapter of the Book: Computational Mechanics in Vehicle Systems Dynamics, 40, pp. 51-70. , Ed. Londres: Taylor & Francis Group plc
dc.descriptionFerreira, E.P., Pandolfi, F., Reinan, T., (2010) Fuzzy Modelling of Multiarticulated Mobile Robots in Complex Maneuvers with Delay: A New Systematic for Movements and Controllers Description, 18. , CBA, Brazil
dc.descriptionKinjo, H., Maeshiro, M., Uezato, E., Yamamoto, T., Adaptive genetic algorithm observer and its application to a trailer truck control system (2006) International Joint Conference Digital
dc.descriptionMiranda, V.M., (2011) Tools for the Development of Full Neural Predictors and Controllers, with Fixed Time Horizon, of Multi-articulated Mobile Robots, , Dissertation (Masters)-PPGEE-UFES, Vitoria, ES
dc.languageen
dc.publisher
dc.relationIEEE International Conference on Control and Automation, ICCA
dc.rightsfechado
dc.sourceScopus
dc.titleFull Neural Predictors, With Fixed Time Horizon, For A Truck-trailer- Trailer Prototype Of A Multi-articulated Robot, In Backward Movements-singular Conditions And Critical Angles
dc.typeActas de congresos


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