EconPapers    
Economics at your fingertips  
 

Data-Driven Adaptive Modelling and Control for a Class of Discrete-Time Robotic Systems Based on a Generalized Jacobian Matrix Initialization

América Berenice Morales-Díaz, Josué Gómez-Casas (), Chidentree Treesatayapun, Carlos Rodrigo Muñiz-Valdez, Jesús Salvador Galindo-Valdés and Jesús Fernando Martínez-Villafañe
Additional contact information
América Berenice Morales-Díaz: Department of Robotics and Advanced Manufacturing, CINVESTAV-Saltillo, Ramos Arizpe 25900, Mexico
Josué Gómez-Casas: Faculty of Engineering, Autonomous University of Coahuila, Arteaga 25350, Mexico
Chidentree Treesatayapun: Department of Robotics and Advanced Manufacturing, CINVESTAV-Saltillo, Ramos Arizpe 25900, Mexico
Carlos Rodrigo Muñiz-Valdez: Faculty of Engineering, Autonomous University of Coahuila, Arteaga 25350, Mexico
Jesús Salvador Galindo-Valdés: Faculty of Engineering, Autonomous University of Coahuila, Arteaga 25350, Mexico
Jesús Fernando Martínez-Villafañe: Faculty of Engineering, Autonomous University of Coahuila, Arteaga 25350, Mexico

Mathematics, 2023, vol. 11, issue 11, 1-19

Abstract: Data technology advances have increased in recent years, especially for robotic systems, in order to apply data-driven modelling and control computations by only considering the input and output signals’ relationship. For a data-driven modelling and control approach, the system is considered unknown. Thus, the initialization values of the system play an important role to obtain a suitable estimation. This paper presents a methodology to initialize a data-driven model using the pseudo-Jacobian matrix algorithm to estimate the model of a mobile manipulator robot. Once the model is obtained, a control law is proposed for the robot end-effector position tasks. To this end, a novel neuro-fuzzy network is proposed as a control law, which only needs to update one parameter to minimize the control error and avoids the chattering phenomenon. In addition, a general stability analysis guarantees the convergence of the estimation and control errors and the tuning of the closed-loop control design parameters. The simulations results validate the performance of the data-driven model and control.

Keywords: data-driven model; Jacobian matrix initialization; robotic system (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/11/11/2555/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/11/2555/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:11:y:2023:i:11:p:2555-:d:1162744

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2555-:d:1162744