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Improvement of Trajectory Tracking by Robot Manipulator Based on a New Co-Operative Optimization Algorithm

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  • Mahmoud Elsisi

    (Industry 4.0 Implementation Center, Center for Cyber-Physical System Innovation, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
    Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo 1162, Egypt)

  • Hatim G. Zaini

    (Computer Engineering Department, College of Computer and Information Technology, Taif University, Al Huwaya, Taif 26571, Saudi Arabia)

  • Karar Mahmoud

    (Department of Electrical Engineering and Automation, Aalto University, FI-00076 Espoo, Finland
    Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt)

  • Shimaa Bergies

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan)

  • Sherif S. M. Ghoneim

    (Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia)

Abstract

The tracking of a predefined trajectory with less error, system-settling time, system, and overshoot is the main challenge with the robot-manipulator controller. In this regard, this paper introduces a new design for the robot-manipulator controller based on a recently developed algorithm named the butterfly optimization algorithm (BOA). The proposed BOA utilizes the neighboring butterflies’ co-operation by sharing their knowledge in order to tackle the issue of trapping at the local optima and enhance the global search. Furthermore, the BOA requires few adjustable parameters via other optimization algorithms for the optimal design of the robot-manipulator controller. The BOA is combined with a developed figure of demerit fitness function in order to improve the trajectory tracking, which is specified by the simultaneous minimization of the response steady-state error, settling time, and overshoot by the robot manipulator. Various test scenarios are created to confirm the performance of the BOA-based robot manipulator to track different trajectories, including linear and nonlinear manners. Besides, the proposed algorithm can provide a maximum overshoot and settling time of less than 1.8101% and 0.1138 s, respectively, for the robot’s response compared to other optimization algorithms in the literature. The results emphasize the capability of the BOA-based robot manipulator to provide the best performance compared to the other techniques.

Suggested Citation

  • Mahmoud Elsisi & Hatim G. Zaini & Karar Mahmoud & Shimaa Bergies & Sherif S. M. Ghoneim, 2021. "Improvement of Trajectory Tracking by Robot Manipulator Based on a New Co-Operative Optimization Algorithm," Mathematics, MDPI, vol. 9(24), pages 1-21, December.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:24:p:3231-:d:702042
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    References listed on IDEAS

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    1. Elsisi, Mahmoud & Bazmohammadi, Najmeh & Guerrero, Josep M. & Ebrahim, Mohamed A., 2021. "Energy management of controllable loads in multi-area power systems with wind power penetration based on new supervisor fuzzy nonlinear sliding mode control," Energy, Elsevier, vol. 221(C).
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    Cited by:

    1. Jing Xie & Bowen Zhang & Tianliang Zhang & Xiangtong Kong, 2025. "Output Feedback Optimal Control for Discrete-Time Singular Systems Driven by Stochastic Disturbances and Markov Chains," Mathematics, MDPI, vol. 13(4), pages 1-20, February.

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