Minimal parametric sensitivity trajectories for nonlinear systems

Alex Ansari, Todd Murphey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Trajectory optimization techniques can be used to minimize error norms on both state and controls with respect to a reference. However, without sufficient control authority, resulting controllers can be sensitive to variations in model parameters. This paper presents a method to incorporate parametric sensitivity in optimal control calculations to develop optimally insensitive trajectories which can be better tracked under open loop and limited gain feedback conditions. As it builds on existing nonlinear optimal control theory, the approach can be easily implemented and applies to a variety of system types. The effectiveness of the technique is demonstrated using a simplified vehicle model. Controllers developed are capable of tracking highly aggressive and dynamically infeasible paths while minimizing sensitivity to variations in modeled friction.

Original languageEnglish (US)
Title of host publication2013 American Control Conference, ACC 2013
Pages5011-5016
Number of pages6
StatePublished - Sep 11 2013
Event2013 1st American Control Conference, ACC 2013 - Washington, DC, United States
Duration: Jun 17 2013Jun 19 2013

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2013 1st American Control Conference, ACC 2013
CountryUnited States
CityWashington, DC
Period6/17/136/19/13

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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