Combined adaptive neural network and regressor-based trajectory tracking control of flexible joint robots

Jorge Montoya-Cháirez, Javier Moreno-Valenzuela*, Víctor Santibáñez, Ricardo Carelli, Fracisco G. Rossomando, Ricardo Pérez-Alcocer

*Autor correspondiente de este trabajo

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

6 Citas (Scopus)

Resumen

By relying on the input–output feedback linearization approach, a novel adaptive controller for flexible joint robots is proposed in this work. First, a model-based controller is developed to get a structure that is useful in the development of the adaptive controller. The adaptive version is developed by using two techniques. To stabilize the output function, an adaptive neural network controller is used, which approximates the non-linear function that contains the uncertainties. The desired rotor position required by the input–output feedback linearization controller is defined with the structure of a link dynamics adaptive regressor-based controller. The main reason to adopt the mentioned structure in the definition of the desired rotor link position is to guarantee its differentiability. Real-time experiment comparisons among the model-based controller, a model-based controller with desired compensation, an adaptive controller based on joint torque feedback, and an adaptive neural network-based controller are carried out. Experimental results support the theory reported in this document and the accuracy of the proposed approach.

Idioma originalInglés
Páginas (desde-hasta)31-50
Número de páginas20
PublicaciónIET Control Theory and Applications
Volumen16
N.º1
DOI
EstadoPublicada - ene. 2022
Publicado de forma externa

Nota bibliográfica

Funding Information:
This work was supported in part by the Consejo Nacional de Ciencia y Tecnología, CONACYT-Fondo Sectorial de Investigación para la Educación under Project A1-S-24762, and in part by CONACYT Project 134534, Secretaría de Investigación y Posgrado-Instituto Politécnico Nacional, México. Proyecto Apoyado por el Fondo Sectorial de Investigación para la Educación. Work partially supported by TecNM projects.

Funding Information:
This work was supported in part by the Consejo Nacional de Ciencia y Tecnología, CONACYT‐Fondo Sectorial de Investigación para la Educación under Project A1‐S‐24762, and in part by CONACYT Project 134534, Secretaría de Investigación y Posgrado‐Instituto Politécnico Nacional, México. Proyecto Apoyado por el Fondo Sectorial de Investigación para la Educación. Work partially supported by TecNM projects.

Publisher Copyright:
© 2021 The Authors. IET Control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology

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