带输入量化的不确定非线性多代理系统的非奇异自适应有限时间共识控制

Yunbiao Jiang, Fuyong Wang, Zhongxin Liu, Zengqiang Chen
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摘要

本文研究了有向通信拓扑中输入量化的非线性多代理系统的分布式共识控制。通过将滤波反步法与神经网络控制相结合,提出了一种非奇异自适应有限时间控制(NAFTC)方案。由于[公式:见正文]的连续性,控制信号的颤振和奇异性问题都得以避免,因此在我们的方案中不存在输入量化的不连续有限时间控制与[公式:见正文]连续有限时间控制之间的矛盾。同时,我们还推导出了滞后量化器输入输出关系的新不等式,它可以简单地处理输入量化,而不需要额外的稳定性分析。此外,我们的方案不需要一些常见的假设,如 Lipschitz 假设和 Holder-continuity 假设。最后,我们还提供了稳定性分析和数值模拟。
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Nonsingular adaptive finite-time consensus control for uncertain nonlinear multi-agent systems with input quantization
This paperinvestigates the distributed consensus control for nonlinear multi-agent systems with input quantization in a directed communication topology. A nonsingular adaptive finite-time control (NAFTC) scheme is proposed by combining the filtered backstepping method with neural network control. Both chattering and singularity problems of the control signals are avoided thanks to its [Formula: see text] continuity, so that the contradiction between discontinuous- and [Formula: see text] continuous finite-time control with input quantization does not exist in our scheme. At the same time, a novel inequality for the input-output relationship of hysteresis quantizer is derived, which can simply handle the input quantization without requiring additional stability analysis. What is more, some common assumptions, such as Lipschitz assumption and Holder-continuity assumption, are not required in our scheme. Finally, stability analysis and numerical simulation are provided.
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