Radial basis function neural network based adaptive fast nonsingular terminal sliding mode controller for piezo positioning stage

This paper presents an adaptive fast nonsingular terminal sliding mode control base on a neural network based approximation technique to control the position of a piezo positioning stage (PSS). The proposed terminal sliding mode control can provide faster convergence and higher precision control whi...

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Bibliographic Details
Published in:International journal of control, automation, and systems 2017, Automation, and Systems, 15(6), , pp.2892-2905
Main Authors: Dinh, To Xuan, Ahn, Kyoung Kwan
Format: Article
Language:English
Subjects:
Adaptive control
Basis functions
Control
Controllers
Engineering
Intelligent Control and Applications
Liapunov functions
Mechatronics
Neural networks
On-line systems
Radial basis function
Robotics
Robust control
Sliding mode control
Stability analysis
Uncertainty
제어계측공학
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Summary:This paper presents an adaptive fast nonsingular terminal sliding mode control base on a neural network based approximation technique to control the position of a piezo positioning stage (PSS). The proposed terminal sliding mode control can provide faster convergence and higher precision control while maintain its robustness to uncertainties. In the proposed control scheme, the combination of the fast-nonsingular terminal sliding mode control and neural network, which can precisely estimate the uncertainties in dynamic of the PSS system by employing an online tuning scheme, is a promising control approach for actuator systems. In addition, the robust control term is adopted to compensate the modeling error and ensure the robustness corresponding to a bounded disturbance. Stability of the closed loop system is analyzed and proved by using special Lyapunov functions. Experiment results strongly confirm the effectiveness of the proposed control method.
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-016-0650-1