Adaptive Robust Motion Control for Hydraulic Actuators With an Adjustable Event Trigger

IF 8.7 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Jixiang Chen;Zhongyang Fei;Litong Lyu;Weiguo Xia;Xi-Ming Sun
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引用次数: 0

Abstract

This article investigates the event-triggered adaptive robust motion control for hydraulic actuators with parametric uncertainties and system nonlinearities. Under the continuous communication condition, the traditional adaptive robust motion controller is recursively presented. In order to reduce the unnecessary bandwidth consumption in the aero-engine networked control platform, an adaptive threshold triggered mechanism according to network resources is developed to synthesize the motion controller. Adjustable threshold parameters are involved to flexibly adjust the data transmission times depending on the network bandwidth occupation. It is proved that with the motion controller and the proposed adjustable threshold triggered mechanism, all the closed-loop system signals are globally bounded, and the hydraulic system output achieves asymptotic tracking to the reference trajectory by virtue of the adaptive technique, the Nussbaum-type and sign functions. Besides, the Zeno behavior is excluded, successfully. Finally, the proposed event-based control scheme is tested and discussed on the aero-engine hardware-in-the-loop (HIL) experiment platform with hydraulic actuators.
带有可调事件触发器的液压执行器的自适应鲁棒运动控制
研究了具有参数不确定性和系统非线性的液压执行器事件触发自适应鲁棒运动控制问题。在连续通信条件下,递归地提出了传统的自适应鲁棒运动控制器。为了减少航空发动机网络化控制平台中不必要的带宽消耗,提出了一种基于网络资源的自适应阈值触发机制来综合运动控制器。提供可调阈值参数,可根据网络带宽占用情况灵活调整数据传输次数。通过运动控制器和所提出的可调阈值触发机构,证明了闭环系统的所有信号都是全局有界的,液压系统的输出利用自适应技术、nussbaum型函数和符号函数实现了对参考轨迹的渐近跟踪。此外,成功地排除了芝诺行为。最后,在航空发动机液压作动器半在环实验平台上对所提出的基于事件的控制方案进行了测试和讨论。
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来源期刊
IEEE Transactions on Systems Man Cybernetics-Systems
IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS
CiteScore
18.50
自引率
11.50%
发文量
812
审稿时长
6 months
期刊介绍: The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.
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