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dc.contributor.authorKolathaya, Shishir
dc.contributor.authorAmes, Aaron D.
dc.date.accessioned2016-05-09T16:07:28Z
dc.date.available2016-05-09T16:07:28Z
dc.date.issued2015
dc.identifier.citationKolathaya, S., & Ames, A. D. (2015). Parameter Sensitivity and Boundedness of Robotic Hybrid Periodic Orbits*. IFAC-PapersOnLine, Volume 48, Issue 27, 2015, pp. 377-382. 5th IFAC Conference on Analysis and Design of Hybrid Systems, October 14-16, 2015, Georgia Tech, Atlanta.en_US
dc.identifier.issn2405-8963
dc.identifier.urihttp://hdl.handle.net/1853/54768
dc.description© 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserveden_US
dc.descriptionDOI: 10.1016/j.ifacol.2015.11.203
dc.description.abstractModel-based nonlinear controllers like feedback linearization and control Lyapunov functions are highly sensitive to the model parameters of the robot. This paper addresses the problem of realizing these controllers in a particular class of hybrid models-systems with impulse effects-through a parameter sensitivity measure. This measure quantifies the sensitivity of a given model-based controller to parameter uncertainty along a particular trajectory. By using this measure, output boundedness of the controller (computed torque+PD) will be analyzed. Given outputs that characterize the control objectives, i.e., the goal is to drive these outputs to zero, we consider Lyapunov functions obtained from these outputs. The main result of this paper establishes the ultimate boundedness of the output dynamics in terms of this measure via these Lyapunov functions under the assumption of stable hybrid zero dynamics. This is demonstrated in simulation on a 5-DOF underactuated bipedal robot.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectHybrid zero dynamicsen_US
dc.subjectParameter sensitivity measureen_US
dc.subjectSystem identificationen_US
dc.titleParameter Sensitivity and Boundedness of Robotic Hybrid Periodic Orbitsen_US
dc.typeArticleen_US
dc.typeProceedings
dc.contributor.corporatenameGeorgia Institute of Technology. Institute for Robotics and Intelligent Machinesen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Electrical and Computer Engineeringen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Mechanical Engineeringen_US
dc.publisher.originalElsevier
dc.identifier.doi10.1016/j.ifacol.2015.11.203
dc.embargo.termsnullen_US


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