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Chaotic Synchronization in Mobile Robots

Author

Listed:
  • Lili Wu

    (School of Intelligent Manufacturing, Zhejiang Guangsha Vocational and Technical University of Construction, Dongyang 322100, China)

  • Dongyun Wang

    (College of Engineering, Zhejiang Normal University, Jinhua 321000, China)

  • Chunwei Zhang

    (Multidisciplinary Center for Infrastructure Engineering, Shenyang University of Technology, Shenyang 110870, China)

  • Ardashir Mohammadzadeh

    (Multidisciplinary Center for Infrastructure Engineering, Shenyang University of Technology, Shenyang 110870, China)

Abstract

Chaos dynamics is an interesting nonlinear effect that can be observed in many chemical, electrical, and mechanical systems. The chaos phenomenon has many applications in various branches of engineering. On the other hand, the control of mobile robots to track unpredictable chaotic trajectories has a valuable application in many security problems and military missions. The main objective in this problem is to design a controller such that the robot tracks a desired chaotic path. In this paper, the concept of synchronization of chaotic systems is studied, and a new type-3 fuzzy system (T3FLS)-based controller is designed. The T3FLS is learned by some new adaptive rules. The new learning scheme of T3FLS helps to better stabilize and synchronize. The suggested controller has a better ability to cope with high-level uncertainties. Because, in addition to the fact that the T3FLSs have better ability in an uncertain environment, the designed compensator also improves the accuracy and robustness. Several simulations show better synchronization and control accuracy of the designed controller.

Suggested Citation

  • Lili Wu & Dongyun Wang & Chunwei Zhang & Ardashir Mohammadzadeh, 2022. "Chaotic Synchronization in Mobile Robots," Mathematics, MDPI, vol. 10(23), pages 1-15, December.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:23:p:4568-:d:991478
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    References listed on IDEAS

    as
    1. Jianfang Lian & Wentao Yu & Kui Xiao & Weirong Liu, 2020. "Cubic Spline Interpolation-Based Robot Path Planning Using a Chaotic Adaptive Particle Swarm Optimization Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-20, February.
    2. Pal, Pikaso & Mukherjee, V. & Alemayehu, Hinsermu & Jin, Gang Gyoo & Feyisa, Gosa, 2021. "Generalized adaptive backstepping sliding mode control for synchronizing chaotic systems with uncertainties and disturbances," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 793-807.
    3. Li, Jiayan & Cao, Jinde & Liu, Heng, 2022. "State observer-based fuzzy echo state network sliding mode control for uncertain strict-feedback chaotic systems without backstepping," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    4. Setoudeh, Farbod & Dezhdar, Mohammad Matin & Najafi, M., 2022. "Nonlinear analysis and chaos synchronization of a memristive-based chaotic system using adaptive control technique in noisy environments," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
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    Citations

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    Cited by:

    1. Lixiong Lin & Zhiping Xu & Jiachun Zheng, 2023. "Predefined Time Active Disturbance Rejection for Nonholonomic Mobile Robots," Mathematics, MDPI, vol. 11(12), pages 1-21, June.

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