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A Sliding-Mode Control Algorithm of Self-Learning and Obstacle Avoidance for Mobile Robots

Received: 29 November 2016     Accepted: 13 December 2016     Published: 14 January 2017
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Abstract

It is generally very difficult to make effective obstacle avoidance for mobile robots, especially in uncertain environments. This article models the obstacle avoidance problem as a nonlinear sliding mode, using the self-learning method of non-linear system. First, a sliding mode algorithm is proposed for state dependent layers of the mobile robots, in which two kinds of boundary layers are included in, namely a sector-shaped layer and a constant layer. Second, a multi-input algorithm based on sliding-mode for self-learning of mobile robots is discussed. Some control rules are built for the self-learning and obstacle avoidance of mobile robots, and the solving steps are also presented. Last, an experiment is designed to verify the proposed model and calculate the sliding- mode control for mobile robots. Some interesting conclusions and future work are indicated at the end of the paper.

Published in Internet of Things and Cloud Computing (Volume 4, Issue 5)
DOI 10.11648/j.iotcc.20160405.11
Page(s) 45-54
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Self-Learning, Sliding-Mode Control, Obstacle Avoidance, Mobile Robots

References
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Cite This Article
  • APA Style

    Tian Tian, Qiuyue Jiang, Zhengying Cai. (2017). A Sliding-Mode Control Algorithm of Self-Learning and Obstacle Avoidance for Mobile Robots. Internet of Things and Cloud Computing, 4(5), 45-54. https://doi.org/10.11648/j.iotcc.20160405.11

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    ACS Style

    Tian Tian; Qiuyue Jiang; Zhengying Cai. A Sliding-Mode Control Algorithm of Self-Learning and Obstacle Avoidance for Mobile Robots. Internet Things Cloud Comput. 2017, 4(5), 45-54. doi: 10.11648/j.iotcc.20160405.11

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    AMA Style

    Tian Tian, Qiuyue Jiang, Zhengying Cai. A Sliding-Mode Control Algorithm of Self-Learning and Obstacle Avoidance for Mobile Robots. Internet Things Cloud Comput. 2017;4(5):45-54. doi: 10.11648/j.iotcc.20160405.11

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  • @article{10.11648/j.iotcc.20160405.11,
      author = {Tian Tian and Qiuyue Jiang and Zhengying Cai},
      title = {A Sliding-Mode Control Algorithm of Self-Learning and Obstacle Avoidance for Mobile Robots},
      journal = {Internet of Things and Cloud Computing},
      volume = {4},
      number = {5},
      pages = {45-54},
      doi = {10.11648/j.iotcc.20160405.11},
      url = {https://doi.org/10.11648/j.iotcc.20160405.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.iotcc.20160405.11},
      abstract = {It is generally very difficult to make effective obstacle avoidance for mobile robots, especially in uncertain environments. This article models the obstacle avoidance problem as a nonlinear sliding mode, using the self-learning method of non-linear system. First, a sliding mode algorithm is proposed for state dependent layers of the mobile robots, in which two kinds of boundary layers are included in, namely a sector-shaped layer and a constant layer. Second, a multi-input algorithm based on sliding-mode for self-learning of mobile robots is discussed. Some control rules are built for the self-learning and obstacle avoidance of mobile robots, and the solving steps are also presented. Last, an experiment is designed to verify the proposed model and calculate the sliding- mode control for mobile robots. Some interesting conclusions and future work are indicated at the end of the paper.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - A Sliding-Mode Control Algorithm of Self-Learning and Obstacle Avoidance for Mobile Robots
    AU  - Tian Tian
    AU  - Qiuyue Jiang
    AU  - Zhengying Cai
    Y1  - 2017/01/14
    PY  - 2017
    N1  - https://doi.org/10.11648/j.iotcc.20160405.11
    DO  - 10.11648/j.iotcc.20160405.11
    T2  - Internet of Things and Cloud Computing
    JF  - Internet of Things and Cloud Computing
    JO  - Internet of Things and Cloud Computing
    SP  - 45
    EP  - 54
    PB  - Science Publishing Group
    SN  - 2376-7731
    UR  - https://doi.org/10.11648/j.iotcc.20160405.11
    AB  - It is generally very difficult to make effective obstacle avoidance for mobile robots, especially in uncertain environments. This article models the obstacle avoidance problem as a nonlinear sliding mode, using the self-learning method of non-linear system. First, a sliding mode algorithm is proposed for state dependent layers of the mobile robots, in which two kinds of boundary layers are included in, namely a sector-shaped layer and a constant layer. Second, a multi-input algorithm based on sliding-mode for self-learning of mobile robots is discussed. Some control rules are built for the self-learning and obstacle avoidance of mobile robots, and the solving steps are also presented. Last, an experiment is designed to verify the proposed model and calculate the sliding- mode control for mobile robots. Some interesting conclusions and future work are indicated at the end of the paper.
    VL  - 4
    IS  - 5
    ER  - 

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Author Information
  • College of Internet of Things Engineering, China Three Gorges University, Yichang, China

  • College of Mechanical-Electronic Engineering, China Three Gorges University, Yichang, China

  • College of Internet of Things Engineering, China Three Gorges University, Yichang, China

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