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dc.contributor.authorPeng, Ya-Fuen_US
dc.contributor.authorHsu, Chun-Felen_US
dc.contributor.authorLin, Chih-Minen_US
dc.contributor.authorLee, Tsu-Tianen_US
dc.date.accessioned2017-04-21T06:48:15Z-
dc.date.available2017-04-21T06:48:15Z-
dc.date.issued2006en_US
dc.identifier.isbn978-1-4244-0099-7en_US
dc.identifier.issn1062-922Xen_US
dc.identifier.urihttp://dx.doi.org/10.1109/ICSMC.2006.385037en_US
dc.identifier.urihttp://hdl.handle.net/11536/135204-
dc.description.abstractThis paper proposes a robust intelligent backsteppingcontrol (RIBC) scheme for the car-following control of a platoon of automated vehicles using a recurrent cerebellar model articulation controller (RCMAC) via the H-infinity control technique, so that the robust tracking performance can be achieved. In the RIBC system, an adaptive RCMAC is used to mimic an ideal backstepping control law and a robust controller is designed to attenuate the effects caused by unmodeled dynamics, disturbances and approximate errors. Moreover, the Taylor linearization technique is employed to derive the linearized model of the RCMAC. The adaptation laws of the RIBC system are derived on the basis of the Lyapunov stability analysis and H-infinity control theory so that the stability of the system can be guaranteed. Finally, the simulation results denominate that the proposed RIBC system can achieve favorable tracking performance for a safe car-following control.en_US
dc.language.isoen_USen_US
dc.titleRobust intelligent backstepping longitudinal control of vehicle platoons with H-infinity tracking performanceen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/ICSMC.2006.385037en_US
dc.identifier.journal2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGSen_US
dc.citation.spage4648en_US
dc.citation.epage+en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000248078505035en_US
dc.citation.woscount1en_US
Appears in Collections:Conferences Paper