Smart structural stability and NN based intelligent control for nonlinear systems

IF 2.1 3区工程技术 Q2 ENGINEERING, CIVIL

Smart Structures and Systems Pub Date : 2021-06-01 DOI:10.12989/SSS.2021.27.6.917

Tim Chen, Ying Huang, C. C. Hung, Suzanne Frias, J. A. Muhammad, Cyj Chen

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引用次数: 4

Abstract

This paper has proposed an intelligent Evolutionary Bat Algorithm (afterward, EBA) Fuzzy NN (Neural Network) controller used to ensure the asymptotic simulation stability of a mathematics nonlinear system for a smart structure. The smart evolutionary fuzzy NN model adopts an NN numerical model and the linear differential inclusion (LDI) concept. Denotation of the nonlinear dynamics is constructed by transforming the nonlinear model into a multi-rule-based sector nonlinear form of mathematics linear numerical models, and implementing a new sufficient mathematics condition whereby the asymptotic simulation stability of the intelligent structure is guaranteed by the Lyapunov mathematics function, linear matrix inequality (LMI). The high frequency is also injected as an auxiliary to stabilize these nonlinear systems. According to the relaxed method injected with dithered auxiliary, the nonlinear system can be guaranteed stable by appropriately regulating the parameters. Finally, there is a numerical resultant example with simulation results which is designated in order to precisely demonstrate the advantages of the smart intelligent controller and the proposed control scheme compared to previous schemes.

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非线性系统的智能结构稳定性与基于神经网络的智能控制

本文提出了一种智能进化蝙蝠算法（EBA）模糊神经网络控制器，用于保证智能结构数学非线性系统的渐近仿真稳定性。智能进化模糊神经网络模型采用了神经网络数值模型和线性微分包含（LDI）概念。通过将非线性模型转化为基于多规则的扇形非线性数学线性数值模型，并实现一个新的充分数学条件，从而通过李雅普诺夫数学函数线性矩阵不等式（LMI）来保证智能结构的渐近模拟稳定性，从而构建了非线性动力学的表示。高频也被注入作为辅助来稳定这些非线性系统。根据引入抖动辅助的松弛方法，通过适当调整参数可以保证非线性系统的稳定。最后，给出了一个带有仿真结果的数值算例，以准确地展示智能控制器和所提出的控制方案与以往方案相比的优势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Smart Structures and Systems 工程技术-工程：机械

CiteScore

6.50

自引率

8.60%

发文量

审稿时长

9 months

期刊介绍： An International Journal of Mechatronics, Sensors, Monitoring, Control, Diagnosis, and Management airns at providing a major publication channel for researchers in the general area of smart structures and systems. Typical subjects considered by the journal include: Sensors/Actuators(Materials/devices/ informatics/networking) Structural Health Monitoring and Control Diagnosis/Prognosis Life Cycle Engineering(planning/design/ maintenance/renewal) and related areas.