A branch-and-bound algorithm for energy-efficient control allocation with applications to planar motion control of electric ground vehicles

Yan Chen, Junmin Wang

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

2 Scopus citations

Abstract

A globally optimal energy-efficient control allocation (EECA) is developed for planar motion control of electric ground vehicles (EGVs) with four in-wheel motors. Different from the distribution processes in previous EECA designs [19][21], which obtained optimal torque distributions locally due to the nonlinear/nonconvex characteristics of EECA formulation, this EECA approach based a branch-and-bound (B&B) method that can make the distributed control actuation achieve the global energy-optimal operating points. Based on a sequence of equivalent problem transformations and a linear relaxation programming, the global optimal programming can be solved by the B&B method through rewriting the EECA formulation into a polynomial fractional optimization problem. Simulation results of different EGV maneuvers indicate that less energy are consumed when the EECA scheme based on the B&B method is applied, in comparison with the energy consumptions of the identical maneuvers with the active-set algorithm.

Original languageEnglish (US)
Title of host publication2012 American Control Conference, ACC 2012
Pages4999-5004
Number of pages6
StatePublished - Nov 26 2012
Externally publishedYes
Event2012 American Control Conference, ACC 2012 - Montreal, QC, Canada
Duration: Jun 27 2012Jun 29 2012

Publication series

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

Other

Other2012 American Control Conference, ACC 2012
CountryCanada
CityMontreal, QC
Period6/27/126/29/12

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    Chen, Y., & Wang, J. (2012). A branch-and-bound algorithm for energy-efficient control allocation with applications to planar motion control of electric ground vehicles. In 2012 American Control Conference, ACC 2012 (pp. 4999-5004). [6314861] (Proceedings of the American Control Conference).