Paper
28 February 2023 Design of fractional-order global sliding mode controller for thermal-structure test based on neural network
Yue Wang, Guangming Zhang, Xiaodong Lv, Gang Wang, Zhiqing Bai
Author Affiliations +
Proceedings Volume 12596, International Conference on Mechatronics Engineering and Artificial Intelligence (MEAI 2022); 125960R (2023) https://doi.org/10.1117/12.2671934
Event: International Conference on Mechatronics Engineering and Artificial Intelligence (MEAI 2022), 2022, Changsha, China
Abstract
In this paper, a Fractional-Order Global Sliding Mode Control (FOGSMC) scheme based on a neural network with approximation property (NNO) is mainly focused on study the Thermal-Structural Test (TST) system. Since the nonlinear dynamic system of the thermal-structure test with quartz lamp is susceptible to external interference and parameter variation, a novel FOGSMC system is designed based on improved fractional order global terminal sliding surface to acquire the desired trajectory, and real time estimation of system disturbance using neural network observer with Gaussian Function, meanwhile, the fractional-order global terminal sliding mode surface based on fractional-order function can effectively weaken the chattering phenomenon of the integer order, simulation studies show the effectiveness of the proposed method.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yue Wang, Guangming Zhang, Xiaodong Lv, Gang Wang, and Zhiqing Bai "Design of fractional-order global sliding mode controller for thermal-structure test based on neural network", Proc. SPIE 12596, International Conference on Mechatronics Engineering and Artificial Intelligence (MEAI 2022), 125960R (28 February 2023); https://doi.org/10.1117/12.2671934
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KEYWORDS
Neural networks

Control systems

Aerodynamics

Lamps

Quartz

Design and modelling

Device simulation

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