Studying various cost functions by nonlinear programming for the control of an underactuated mechanical system

Tamás Faitli, J. Tar

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The traditional “Receding Horizon Controller (RHC)” is a heuristic approach based on the concept of “Nonlinear Programming (NP)” that in the most general cases applies Lagrange’s “Reduced Gradient (RG)” method. Since its realization requires a huge amount of numerical calculations, in the practice it is often restricted to quadratic cost functions and “Linear Time Invariant (LTI)” approximation of the dynamic model of the controlled system as “Linear Quadratic Regulator (LQR)”. To release these restrictions a novel approach was recently invented that directly drives the gradient of the “auxiliary function” near zero by replacing the RG with a fixed point-based iteration. It was also shown that the same iteration technique allows the introduction of an “Adaptive Receding Horizon Controller (ARHC)”. Since the convergence of the ARHC strongly depends on the structure of the cost contributions in this paper the operation of the classic RG-based RHC is investigated in the control of the “TORA” system that is a popular paradigm for benchmarking purposes. Conclusions are drawn for the allowable or recommended parameter settings for the cost contributions.

Original languageEnglish
Title of host publicationMechanisms and Machine Science
PublisherSpringer Netherlands
Pages389-397
Number of pages9
DOIs
Publication statusPublished - Jan 1 2019

Publication series

NameMechanisms and Machine Science
Volume67
ISSN (Print)2211-0984
ISSN (Electronic)2211-0992

Fingerprint

Nonlinear programming
Cost functions
Controllers
Gradient methods
Benchmarking
Costs
Dynamic models

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering

Cite this

Faitli, T., & Tar, J. (2019). Studying various cost functions by nonlinear programming for the control of an underactuated mechanical system. In Mechanisms and Machine Science (pp. 389-397). (Mechanisms and Machine Science; Vol. 67). Springer Netherlands. https://doi.org/10.1007/978-3-030-00232-9_41

Studying various cost functions by nonlinear programming for the control of an underactuated mechanical system. / Faitli, Tamás; Tar, J.

Mechanisms and Machine Science. Springer Netherlands, 2019. p. 389-397 (Mechanisms and Machine Science; Vol. 67).

Research output: Chapter in Book/Report/Conference proceedingChapter

Faitli, T & Tar, J 2019, Studying various cost functions by nonlinear programming for the control of an underactuated mechanical system. in Mechanisms and Machine Science. Mechanisms and Machine Science, vol. 67, Springer Netherlands, pp. 389-397. https://doi.org/10.1007/978-3-030-00232-9_41
Faitli T, Tar J. Studying various cost functions by nonlinear programming for the control of an underactuated mechanical system. In Mechanisms and Machine Science. Springer Netherlands. 2019. p. 389-397. (Mechanisms and Machine Science). https://doi.org/10.1007/978-3-030-00232-9_41
Faitli, Tamás ; Tar, J. / Studying various cost functions by nonlinear programming for the control of an underactuated mechanical system. Mechanisms and Machine Science. Springer Netherlands, 2019. pp. 389-397 (Mechanisms and Machine Science).
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