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Adaptive Fuzzy Finite-time Control for Uncertain Nonlinear Systems with Dead-zone Input

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  • Intelligent Control and Applications
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Abstract

This paper presents a novel adaptive finite-time tracking control scheme for nonlinear systems. During the design process of control scheme, dead-zone input nonlinearity phenomena existing in the actuator is taken into account. Fuzzy logic systems are adopted to approximate the unknown nonlinear functions. This paper provides a new finite-time stability criterion, making the adaptive tracking control scheme more suitable in the practice than traditional methods. Under the presented controller, the desired system performance is realized in finite time. Finally, the validity and effectiveness of the proposed control method is validated by two examples.

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Author information

Authors and Affiliations

  1. College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, Shandong, P. R. China

    Wenshun Lv & Fang Wang

  2. School of Automation, Nanjing University of Science and Technology, Nanjing, Jiangsu, P. R. China

    Wenshun Lv

  3. School of Applied Mathematics, Guangdong University of Technology, Guangzhou, P. R. China

    Lili Zhang

Authors
  1. Wenshun Lv
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  2. Fang Wang
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  3. Lili Zhang
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Corresponding author

Correspondence to Fang Wang.

Additional information

Recommended by Associate Editor Do Wan Kim under the direction of Editor Jessie (Ju H.) Park. This work was supported partially by the National Natural Science Foundation of China (Grant Nos. 61503223 and 61603098), in part by the Project of Shandong Province Higher Educational Science and Technology Program (J15LI09), and in part by China Postdoctoral Science Foundation-funded project 2016M592140, and partially by Shandong innovation postdoctoral program 201603066, and partially by the SDUST Research Fund (2014TDJH102).

Wenshun Lv received his B.S. degree from Shandong University of Science and Technology, China, in 2015. He is currently pursuing an M.S. degree with the College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China. His research interests include fuzzy control, neural network control, backstepping control, and adaptive control.

Fang Wang received his B.S. degree from the Qufu Normal University, Qufu, China, an M.S. degree from Shandong Normal University, Jinan, China, and a Ph.D. degree from Guangdong University of Technology, Guangzhou, China, in 1997, 2004, and 2015, respectively. Since 2005, she has been at the Shandong University of Science and Technology, Qingdao, China. Her current research interests include stochastic nonlinear control systems, multi-agent systems, quantized control, and adaptive fuzzy control.

Lili Zhang received her M.S. degree in applied mathematics from University of Science and Technology Beijing, Beijing, P. R. China, in 2004, and her Ph.D degree in school of automation, Guangdong University of Technology, Guangzhou, China, in 2014. She is currently an associate professor in School of Applied Mathematics, Guangdong University of Technology, Guangzhou, China. Her research interests include control and synchronization for complex dynamical networks and chaotic systems.

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Lv, W., Wang, F. & Zhang, L. Adaptive Fuzzy Finite-time Control for Uncertain Nonlinear Systems with Dead-zone Input. Int. J. Control Autom. Syst. 16, 2549–2558 (2018). https://doi.org/10.1007/s12555-018-0118-6

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  • DOI: https://doi.org/10.1007/s12555-018-0118-6

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