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Neural Network Based Control of Four-Bar Mechanism with Variable Input Velocity

Author

Listed:
  • R. Peón-Escalante

    (Faculty of Engineering, University of Yucatan, Mérida 97000, Mexico)

  • Manuel Flota-Bañuelos

    (Faculty of Engineering, University of Yucatan, Mérida 97000, Mexico)

  • Roberto Quintal-Palomo

    (Faculty of Engineering, University of Yucatan, Mérida 97000, Mexico)

  • Luis J. Ricalde

    (Faculty of Engineering, University of Yucatan, Mérida 97000, Mexico)

  • F. Peñuñuri

    (Faculty of Engineering, University of Yucatan, Mérida 97000, Mexico)

  • B. Cruz Jiménez

    (Faculty of Engineering, University of Yucatan, Mérida 97000, Mexico)

  • J. Avilés Viñas

    (Faculty of Engineering, University of Yucatan, Mérida 97000, Mexico)

Abstract

For control applications, the angular velocity of the drive crank of a four-bar mechanism is traditionally assumed to be constant. In this paper, we propose control of variable velocity of the drive crank to obtain the desired output motions for the coupler point. To estimate the reference trajectory for the crank velocity, a neural network is trained with data from the kinematic model. The control law is designed from feedback linearization of the tracking error dynamics and a Proportional–Integral–Derivative (PID) controller. The applicability of the proposed scheme is validated through simulations for three variable speed profiles, obtaining excellent results from the system.

Suggested Citation

  • R. Peón-Escalante & Manuel Flota-Bañuelos & Roberto Quintal-Palomo & Luis J. Ricalde & F. Peñuñuri & B. Cruz Jiménez & J. Avilés Viñas, 2023. "Neural Network Based Control of Four-Bar Mechanism with Variable Input Velocity," Mathematics, MDPI, vol. 11(9), pages 1-17, May.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:9:p:2148-:d:1138941
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    References listed on IDEAS

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    1. David Prentice, 2016. "From the Editor," Economic Papers, The Economic Society of Australia, vol. 35(1), pages 1-1, March.
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