Tikhonov regularization based control allocation for underactuated input-affine systems

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dc.creatorJúnio Eduardo Demorais
dc.creatorDaniel N. Cardoso
dc.creatorGuilherme Vianna Raffo
dc.date.accessioned2025-06-02T13:15:17Z
dc.date.accessioned2025-09-09T01:26:11Z
dc.date.available2025-06-02T13:15:17Z
dc.date.issued2023
dc.identifier.doihttps://doi.org/10.1109/LARS/SBR/WRE59448.2023.10332966
dc.identifier.urihttps://hdl.handle.net/1843/82689
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofLatin American Robotics Symposium (LARS 2023) / Brazilian Symposium on Robotics (SBR 2023) / Workshop on Robotics in Education (WRE 2023)
dc.rightsAcesso Restrito
dc.subjectSistemas não lineares
dc.subject.otherCouplings , Additive noise , Conferences , Education , Manipulators , Control systems , Resource management
dc.subject.otherControl allocation , Underactuated systems , Non-linear systems
dc.subject.otherWeight Decay , Control Allocation , Underactuated Systems , Classical Methods , Nonlinear Systems , Systematic Method , Mechanical Systems , Additional Term , Input Vector , Residual Error , Moore Penrose Inverse , Degrees Of Freedom , Optimization Problem , Actuator , Optimal Control , Diagonal Matrix , Weight Matrix , Effect Of Noise , Beginning Of The Experiment , Control Input , Unmanned Aerial Vehicles , Class Of Systems , Control Input Vector , Singular Value Decomposition , Nonlinear Control , Lagrange Equations , Italic Letters , Redundant System , Pseudo-inverse Matrix , Off-diagonal
dc.titleTikhonov regularization based control allocation for underactuated input-affine systems
dc.typeArtigo de evento
local.citation.epage384
local.citation.spage379
local.description.resumoThis paper proposes a novel control allocation method for underactuated input-affine nonlinear mechanical systems, based on the Tikhonov regularization. A hardware-in-the-loop experiment is conducted using an unmanned aerial manipulator to corroborate the effectiveness of the proposed method. The results demonstrate that, in comparison with the classic Moore-Penrose pseudo-inverse control allocation method, the proposed Tikhonov regularization-based control allocation is computationally faster and attenuates additive noise terms within the generalized input vector. Besides, it reduces the residual error between the desired and applied generalized input when the input coupling matrix is ill-posed.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELÉTRICA
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://ieeexplore.ieee.org/document/10332966

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