Abstract
In this study, we develop an adaptive neural network based boundary control method for a flexible marine riser system with unknown nonlinear disturbances and output constraints to suppress vibrations. We begin with describing the dynamic behavior of the riser system using a distributed parameter system with partial differential equations. To compensate for the effect of nonlinear disturbances, we construct a neural network based boundary controller using a radial basis neural network to reduce vibrations. Under the proposed boundary controller, the state of the riser is guaranteed to be uniformly bounded based on the Lyapunov method. The proposed methodology provides a way to integrate neural networks into boundary control for other flexible robotic manipulator systems. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed control method.
摘要
针对具有未知非线性扰动和输出限制的柔性海洋立管系统, 提出一种基于自适应神经网络的边界控制方法抑制振动. 首先, 通过偏微分方程分布参数系统描述柔性海洋立管系统的动态特性. 为补偿非线性扰动对系统影响, 利用径向基神经网络构造一个基于神经网络的边界控制器以减少振动. 在所提边界控制器下, 基于李亚普诺夫方法, 保证柔性海洋立管系统一致有界. 该方法为其他柔性机器人系统的边界控制提供了一种集成神经网络的思路. 最后, 通过数值仿真验证所提方法的有效性.
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Contributions
Chuyang YU and Xuyang LOU designed the research. Chuyang YU processed the data. Chuyang YU, Xuyang LOU, and Yifei MA drafted the paper. Qian YE and Jinqi ZHANG helped organize and polish the paper. Yifei MA, Qian YE, and Xuyang LOU checked the proofs. Qian YE, Chuyang YU, Xuyang LOU, and Yifei MA revised and finalized the paper.
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Chuyang YU, Xuyang LOU, Yifei MA, Qian YE, and Jinqi ZHANG declare that they have no conflict of interest.
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Project supported by the Natural Science Foundation of Jiangsu Province, China (No. BK20201340), the 333 High-level Talents Training Project of Jiangsu Province, China, and the Blue Project for Colleges and Universities of Jiangsu Province, China
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Proof S1 Proof of Lemma 3
Proof S2 Proof of Theorem 2
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Yu, C., Lou, X., Ma, Y. et al. Adaptive neural network based boundary control of a flexible marine riser system with output constraints. Front Inform Technol Electron Eng 23, 1229–1238 (2022). https://doi.org/10.1631/FITEE.2100586
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DOI: https://doi.org/10.1631/FITEE.2100586
Key words
- Marine riser system
- Partial differential equation
- Neural network
- Output constraint
- Boundary control
- Unknown disturbance