Backstepping Output Feedback Control for the Stochastic Nonlinear System Based on Variable Function Constraints with the Subsea Intelligent Electroexecution Robot System

Long-Chuan Guo, Jing Ni, Jing-Biao Liu, Xiang-Kun Fang, Qing-Hua Meng, Yu-Dong Peng and Sergey Dashkovskiy

Complexity, 2021, vol. 2021, 1-15

Abstract: The output feedback controller is designed for a class of stochastic nonlinear systems that satisfy uncertain function growth conditions for the first time. The multivariate function growth condition has greatly relaxed the restrictions on the drift and diffusion terms in the original stochastic nonlinear system. Here, we cleverly handle the problem of uncertain functions in the scaling process through the function maxima theory so that the Ito differential system can achieve output stabilization through Lyapunov function design and the solution of stochastic nonlinear system objects satisfies the existence of uniqueness, ensuring that the system is globally asymptotically stable in the sense of probability. Furthermore, it is concluded that the system is inversely optimally stable in the sense of probability. Finally, we apply the theoretical results to the practical subsea intelligent electroexecution robot control system and obtain good results.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:8856608

DOI: 10.1155/2021/8856608

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