论文成果
Controller design for nonlinear systems subject to both input saturation and asymmetry time-varying state constraints: A novel network-based approach
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关键字:ADAPTIVE TRACKING CONTROL; FEEDBACK SYSTEMS; NEURAL-CONTROL
摘要:In this article, the issues of asymmetric input saturation and asymmetric time-varying state constraints are integrated into nonlinear systems for the first time, and a new adaptive tracking control strategy is proposed based on the multi-dimensional Taylor network (MTN) method. Firstly, by introducing a continuous auxiliary function, the input saturation is transformed into a smooth model with bounded error. Secondly, MTNs are employed to estimate nonlinear functions, asymmetric barrier Lyapunov functions (ABLFs) are constructed to make all state variables meet asymmetric constraints, and then a novel control scheme with simple structure is developed via backstepping. Thirdly, according to the Lyapunov stability theory, it is proved that all signals in the closed-loop systems are bounded, and all state variables do not violate the constraints. Finally, three examples show the effectiveness of the proposed scheme.
卷号:36
期号:12
是否译文:

朱善良

教授 硕士生导师

教师拼音名称:zhushanliang

学历:博士研究生

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联系方式:zhushanliang@qust.edu.cn

学位:工学博士

所属院系:数理学院

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