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A New Adaptive RISE Feedforward Approach based on Associative Memory Neural Networks for the Control of PKMs

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Abstract

In this paper, a RISE (Robust Integral of the Sign Error) controller with adaptive feedforward compensation terms based on Associative Memory Neural Network (AMNN) type B-Spline is proposed to regulate the positioning of a Delta Parallel Robot (DPR) with three degrees of freedom. Parallel Kinematic Manipulators (PKMs) are highly nonlinear systems, so the design of a suitable control scheme represents a significant challenge given that these kinds of systems are continually dealing with parametric and non-parametric uncertainties and external disturbances. The main contribution of this work is the design of an adaptive feedforward compensation term using B-Spline Neural Networks (BSNNs). They make an on-line approximation of the DPR dynamics and integrates it into the control loop. The BSNNs’ functions are bounded according to the extreme values of the desired joint space trajectories that are the BSNNs’ inputs, and their weights are on-line adjusted by gradient descend rules. In order to evaluate the effectiveness of the proposed control scheme with respect to the standard RISE controller, numerical simulations for different case studies under different scenarios were performed.

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Acknowledgments

Thanks to the Program of Support to the development of higher education (PADES), agreement No 2018-13-011-047. Additionally, J. Escorcia thanks to The Mexican Council of Science and Technology (CONACYT); Award no. 593804.

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Authors and Affiliations

  1. Universidad Politécnica de Tulancingo, Calle Ingenierías No. 100, C.P. 43629, Tulancingo, Hidalgo, México

    Jonatan Martín Escorcia-Hernández & José Humberto Arroyo-Núñez

  2. Facultad de Ingeniería. Universidad La Salle México, Benjamin Franklin No. 45, C.P. 06140, Ciudad de México, México

    Hipólito Aguilar-Sierra

  3. Departamento de Posgrado, UPAEP, Universidad Popular Autónoma del Estado de Puebla, C.P. 72410, Puebla, México

    Omar Aguilar-Mejia

  4. CNRS, LIRMM,, University of Montpellier, Montpellier, France

    Ahmed Chemori

Authors
  1. Jonatan Martín Escorcia-Hernández
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  2. Hipólito Aguilar-Sierra
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  3. Omar Aguilar-Mejia
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  4. Ahmed Chemori
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  5. José Humberto Arroyo-Núñez
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Correspondence to Hipólito Aguilar-Sierra.

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Escorcia-Hernández, J.M., Aguilar-Sierra, H., Aguilar-Mejia, O. et al. A New Adaptive RISE Feedforward Approach based on Associative Memory Neural Networks for the Control of PKMs. J Intell Robot Syst 100, 827–847 (2020). https://doi.org/10.1007/s10846-020-01242-9

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  • DOI: https://doi.org/10.1007/s10846-020-01242-9

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