Adaptive fractional PIλDμ sliding mode control method for speed control of spherical robot

被引：0
作者：
Zhou T. [1 ]
Xu Y.-G. [1 ]
Wu B. [1 ]
机构：
[1] School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing
来源：
Wu, Bin (bwu@bjtu.edu.cn) | 1600年 / Editorial Board of Jilin University卷 / 51期
关键词：
Adaptive control; Control theory; Fractional sliding mode; Speed control; Spherical robot;
D O I：
10.13229/j.cnki.jdxbgxb20191174
中图分类号：
学科分类号：
摘要：
The traditional hierarchical sliding mode control method applied directly to the spherical robot speed control will cause a long adjustment time and a large overshoot, which is hard to meet the requirements in practical application. In this paper, a new sliding surface with fractional order PIλDμ structure is proposed by introducing a derivative element and fractional order calculus. The asymptotic stability condition of the sliding surface is given. Based on the new fractional PIλDμ sliding surface, a velocity controller for the linear motion of the spherical robot is designed. Furthermore, an adaptive law is used to estimate the unknown rolling friction. The simulation results show that the new adaptive fractional sliding mode controller designed in this paper presents a better control performance and stronger robustness compared to the conventional one. Besides, the new controller can accurately estimate the unknown rolling friction. © 2021, Jilin University Press. All right reserved.
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页码：728 / 737
页数：9
相关论文
共 28 条
  • [1] Zhan Q, Cai Y, Yan C X., Design, analysis and experiments of an omni-directional spherical robot, 2011 IEEE International Conference on Robotics and Automation, pp. 9-13, (2011)
  • [2] Mattias S, Mathias B, Alessandro S, Et al., An autonomous spherical robot for security tasks, Proceedings of the 2006 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety, pp. 51-55, (2006)
  • [3] Wang H Q, Liu P X, Xie X J, Et al., Adaptive fuzzy asymptotical tracking control of nonlinear systems with unmodeled dynamics and quantized actuator
  • [4] Liu D L, Sun H X, Jia Q X., A family of spherical mobile robot: driving ahead motion control by feedback linearization, 2008 2nd International Symposium on Systems and Control in Aerospace and Astronautics, pp. 1-6, (2008)
  • [5] Lin C M, Mon Y J., Decoupling control by hierarchical fuzzy sliding-mode controller, IEEE Transactions on Control Systems Technology, 13, 4, pp. 593-598, (2005)
  • [6] Wu Y M, Sun N, Chen H, Et al., Nonlinear time-optimal trajectory planning for varying-rope-length overhead cranes, Assembly Automation, 38, 5, pp. 587-594, (2018)
  • [7] Yang C G, Li Z J, Cui R X, Et al., Neural network-based motion control of an underactuated wheeled inverted pendulum model, IEEE Transactions on Neural Networks and Learning Systems, 25, 11, pp. 2004-2016, (2014)
  • [8] Cai Y, Zhan Q, Xi X., Neural network control for the linear motion of a spherical mobile robot, International Journal of Advanced Robotic Systems, 8, 4, pp. 79-87, (2011)
  • [9] Utkin V., Variable structure systems with sliding modes, IEEE Transactions on Automatic Control, 22, 2, pp. 212-222, (1977)
  • [10] Xu R, Umit O., Sliding mode control of a class of underactuated systems, Automatica, 44, 1, pp. 233-241, (2008)
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