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Extended state observer-based adaptive sliding mode control of differential-driving mobile robot with uncertainties

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Abstract

Based on the uncertain nonlinear kinematic model of the differential-driving mobile robots, an adaptive sliding mode control method is used to design a controller for trajectory tracking of the differential-driving mobile robots with unknown parameter variations and external disturbances. The total uncertainties of the robot are estimated online by an improved linear extended state observer (ESO) with the error compensating term. The adaptive sliding mode controller with the switching gain is adjustable real-time online is developed by selecting the appropriate PID-type sliding surface. The convergence of the tracking errors for wheeled mobile robots is proved by the Lyapunov stability theory. Moreover, the simulation and real experiment results all show that the effectiveness and superiority of the proposed the adaptive sliding mode control method, in comparison with the traditional sliding model control and backstepping control method.

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Acknowledgments

This work was supported by the National Natural Science Foundation (No. U1404614), the Henan Province Education Department Foundation (Nos. 14B120003, 15A413005), the Nanyang Normal University Foundation (Nos. ZX2014085, ZX2015007), the Henan Province Scientific and Technological Foundation (Nos. 122102210403, 142300410184).

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Authors and Affiliations

  1. College of Physical and Electronic Engineering, Nanyang Normal University, Nanyang, 473061, China

    Mingyue Cui, Wei Liu, Hongzhao Liu, Hualong Jiang & Zhipeng Wang

  2. Oil equipment intelligent control engineering laboratory of Henan province, Henan, Nanyang, 473061, China

    Mingyue Cui, Wei Liu, Hongzhao Liu & Zhipeng Wang

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  1. Mingyue Cui
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  2. Wei Liu
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  3. Hongzhao Liu
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  4. Hualong Jiang
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  5. Zhipeng Wang
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Correspondence to Mingyue Cui.

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Cui, M., Liu, W., Liu, H. et al. Extended state observer-based adaptive sliding mode control of differential-driving mobile robot with uncertainties. Nonlinear Dyn 83, 667–683 (2016). https://doi.org/10.1007/s11071-015-2355-z

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  • DOI: https://doi.org/10.1007/s11071-015-2355-z

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