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A New Motion Tracking Controller with Feedforward Compensation for Robot Manipulators Based on Sectorial Fuzzy Control and Adaptive Neural Networks

Author

Listed:
  • Andres Pizarro-Lerma

    (Instituto Tecnológico de Sonora, Ciudad Obregón C.P. 85000, Sonora, Mexico)

  • Victor Santibañez

    (Tecnológico Nacional de Mexico/Instituto Tecnológico de La Laguna, Torreón C.P. 27000, Coahuila, Mexico)

  • Ramon Garcia-Hernandez

    (Tecnológico Nacional de Mexico/Instituto Tecnológico de La Laguna, Torreón C.P. 27000, Coahuila, Mexico)

  • Jorge Villalobos-Chin

    (Facultad de Ingeniería, Ciencias y Arquitectura de la Universidad Juárez del Estado de Durango, Gómez Palacio C.P. 35070, Durango, Mexico)

  • Javier Moreno-Valenzuela

    (Centro de Investigación y Desarrollo de Tecnología Digital, Instituto Politécnico Nacional, Tijuana C.P. 22435, Baja California, Mexico)

Abstract

A novel trajectory tracking control approach for robot manipulators that uses adaptive neural network feedforward compensation plus a sectorial fuzzy controller is presented. We conduct simulation and real-time experiments comparing it with two previously published control schemes: a Proportional–Derivative (PD) plus feedforward compensation controller model, and a sectorial fuzzy control plus feedforward compensation model. The proposed controller shows a faster transient response and better steady-state angular error performance than its counterparts, and it maintains its tolerance to parameter deviation, a main characteristic of fuzzy controllers; furthermore, it excludes the need for knowledge of the robot manipulator model to achieve excellent results. A formal stability analysis of the proposed controller in a closed loop with the robot manipulator guarantees that position and velocity errors converge to zero and all signals are uniformly bounded.

Suggested Citation

  • Andres Pizarro-Lerma & Victor Santibañez & Ramon Garcia-Hernandez & Jorge Villalobos-Chin & Javier Moreno-Valenzuela, 2025. "A New Motion Tracking Controller with Feedforward Compensation for Robot Manipulators Based on Sectorial Fuzzy Control and Adaptive Neural Networks," Mathematics, MDPI, vol. 13(6), pages 1-25, March.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:6:p:977-:d:1613474
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    References listed on IDEAS

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    1. Vesna Antoska Knights & Olivera Petrovska & Jasenka Gajdoš Kljusurić, 2024. "Nonlinear Dynamics and Machine Learning for Robotic Control Systems in IoT Applications," Future Internet, MDPI, vol. 16(12), pages 1-23, November.
    2. Andres Pizarro-Lerma & Victor Santibañez & Ramon Garcia-Hernandez & Jorge Villalobos-Chin, 2021. "Sectorial Fuzzy Controller Plus Feedforward for the Trajectory Tracking of Robotic Arms in Joint Space," Mathematics, MDPI, vol. 9(6), pages 1-40, March.
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