24
IRUS Total
Downloads
  Altmetric

An integral penalty-barrier direct transcription method for optimal control

File Description SizeFormat 
PBF_Martin_Eric_CDC2020.pdfAccepted version842.94 kBAdobe PDFView/Open
Title: An integral penalty-barrier direct transcription method for optimal control
Authors: Neuenhofen, MP
Kerrigan, E
Item Type: Conference Paper
Abstract: Some direct transcription methods can fail to converge, e.g. when there are singular arcs. We recently introduced a convergent direct transcription method for optimal control problems, called the penalty-barrier finite element method (PBF). PBF converges under very weak assumptions on the problem instance. PBF avoids the ringing between collocation points, for example, by avoiding collocation entirely. Instead, equality path constraint residuals are forced to zero everywhere by an integral quadratic penalty term. We highlight conceptual differences between collocation- and penalty-type direct transcription methods. Theoretical convergence results for both types of methods are reviewed and compared. Formulas for implementing PBF are presented, with details on the formulation as a nonlinear program (NLP), sparsity and solution. Numerical experiments compare PBF against several collocation methods with regard to robustness, accuracy, sparsity and computational cost. We show that the computational cost, sparsity and construction of the NLP functions are roughly the same as for orthogonal collocation methods of the same degree and mesh. As an advantage, PBF converges in cases where collocation methods fail. PBF also allows one to trade off computational cost, optimality and violation of differential and other equality equations against each other.
Issue Date: 11-Jan-2021
Date of Acceptance: 16-Jul-2020
URI: http://hdl.handle.net/10044/1/83171
DOI: 10.1109/CDC42340.2020.9304216
Publisher: IEEE
Start Page: 456
End Page: 463
Journal / Book Title: 2020 59th IEEE Conference on Decision and Control (CDC)
Copyright Statement: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Conference Name: 59th IEEE Conference on Decision and Control 2020
Publication Status: Published
Start Date: 2020-12-14
Finish Date: 2020-12-18
Conference Place: South Korea
Online Publication Date: 2021-01-11
Appears in Collections:Electrical and Electronic Engineering
Faculty of Engineering