International Journal of Control, Automation and Systems 2018; 16(5): 2549-2558
Published online September 20, 2018
https://doi.org/10.1007/s12555-018-0118-6
© The International Journal of Control, Automation, and Systems
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."
Keywords Adaptive tracking control, backstepping, dead-zone input, finite-time stability, fuzzy logic systems.
International Journal of Control, Automation and Systems 2018; 16(5): 2549-2558
Published online October 1, 2018 https://doi.org/10.1007/s12555-018-0118-6
Copyright © The International Journal of Control, Automation, and Systems.
Wenshun Lv, Fang Wang*, and Lili Zhang
Shandong University of Science and Technology
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."
Keywords: Adaptive tracking control, backstepping, dead-zone input, finite-time stability, fuzzy logic systems.
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