Research on parallel control of CMAC and PD based on U model

In this paper, the nonlinear U model with time-varying coefficients is investigated and the transformation of the nonlinear model is accomplished by the Newton iterative algorithm. Based on the nonlinear U model, a control algorithm with cerebellar model articulation controller and proportional deri...

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Autores principales:	Fengxia Xu, Junhua Xu, Jiaqi Zhang, Chunda Zhang, Zifei Wang
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2021
Materias:	nonlinear u model newton iteration cmac neural network nonlinear pd Control engineering systems. Automatic machinery (General) TJ212-225 Automation T59.5
Acceso en línea:	https://doaj.org/article/13ca4c89c23c4a82a95c73a8200f46a3
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spelling	oai:doaj.org-article:13ca4c89c23c4a82a95c73a8200f46a32021-11-04T15:00:41ZResearch on parallel control of CMAC and PD based on U model0005-11441848-338010.1080/00051144.2021.1954782https://doaj.org/article/13ca4c89c23c4a82a95c73a8200f46a32021-10-01T00:00:00Zhttp://dx.doi.org/10.1080/00051144.2021.1954782https://doaj.org/toc/0005-1144https://doaj.org/toc/1848-3380In this paper, the nonlinear U model with time-varying coefficients is investigated and the transformation of the nonlinear model is accomplished by the Newton iterative algorithm. Based on the nonlinear U model, a control algorithm with cerebellar model articulation controller and proportional derivative (PD) in parallel is proposed. The algorithm learns online through a neural network while optimizing the output of the PD, which ultimately enables the actual output of the system to track up to the desired output. Considering that the nonlinear object has the characteristic of rapid change with time, the article improves the PD algorithm to nonlinear PD control algorithm to complete the design of the system. The algorithm automatically adjusts the weights according to the error magnitude to complete the controller parameter adjustment, thus reducing the error of the system. The simulation results show that the nonlinear PD algorithm is better than the PD algorithm, meanwhile, the tracking speed and control precision of the system are improved.Fengxia XuJunhua XuJiaqi ZhangChunda ZhangZifei WangTaylor & Francis Grouparticlenonlinear u modelnewton iterationcmac neural networknonlinear pdControl engineering systems. Automatic machinery (General)TJ212-225AutomationT59.5ENAutomatika, Vol 62, Iss 3-4, Pp 331-338 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	nonlinear u model newton iteration cmac neural network nonlinear pd Control engineering systems. Automatic machinery (General) TJ212-225 Automation T59.5
spellingShingle	nonlinear u model newton iteration cmac neural network nonlinear pd Control engineering systems. Automatic machinery (General) TJ212-225 Automation T59.5 Fengxia Xu Junhua Xu Jiaqi Zhang Chunda Zhang Zifei Wang Research on parallel control of CMAC and PD based on U model
description	In this paper, the nonlinear U model with time-varying coefficients is investigated and the transformation of the nonlinear model is accomplished by the Newton iterative algorithm. Based on the nonlinear U model, a control algorithm with cerebellar model articulation controller and proportional derivative (PD) in parallel is proposed. The algorithm learns online through a neural network while optimizing the output of the PD, which ultimately enables the actual output of the system to track up to the desired output. Considering that the nonlinear object has the characteristic of rapid change with time, the article improves the PD algorithm to nonlinear PD control algorithm to complete the design of the system. The algorithm automatically adjusts the weights according to the error magnitude to complete the controller parameter adjustment, thus reducing the error of the system. The simulation results show that the nonlinear PD algorithm is better than the PD algorithm, meanwhile, the tracking speed and control precision of the system are improved.
format	article
author	Fengxia Xu Junhua Xu Jiaqi Zhang Chunda Zhang Zifei Wang
author_facet	Fengxia Xu Junhua Xu Jiaqi Zhang Chunda Zhang Zifei Wang
author_sort	Fengxia Xu
title	Research on parallel control of CMAC and PD based on U model
title_short	Research on parallel control of CMAC and PD based on U model
title_full	Research on parallel control of CMAC and PD based on U model
title_fullStr	Research on parallel control of CMAC and PD based on U model
title_full_unstemmed	Research on parallel control of CMAC and PD based on U model
title_sort	research on parallel control of cmac and pd based on u model
publisher	Taylor & Francis Group
publishDate	2021
url	https://doaj.org/article/13ca4c89c23c4a82a95c73a8200f46a3
work_keys_str_mv	AT fengxiaxu researchonparallelcontrolofcmacandpdbasedonumodel AT junhuaxu researchonparallelcontrolofcmacandpdbasedonumodel AT jiaqizhang researchonparallelcontrolofcmacandpdbasedonumodel AT chundazhang researchonparallelcontrolofcmacandpdbasedonumodel AT zifeiwang researchonparallelcontrolofcmacandpdbasedonumodel
_version_	1718444756310163456

Research on parallel control of CMAC and PD based on U model

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