Adaptive output feedback fault-tolerant control for a class of nonlinear systems based on a sensor fusion mechanism

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS ISA transactions Pub Date : 2025-01-01 DOI:10.1016/j.isatra.2024.11.014
Chen Sun , Yan Lin , Qingrui Meng , Lin Li
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Abstract

This paper investigates an output feedback adaptive fault-tolerant tracking control for a class of nonlinear systems with system nonlinearities, sensor failures and external disturbances, in which sensor redundancy is employed to enhance measurement reliability. A sensor fusion mechanism, together with a novel history-based weighted average algorithm is first designed to fuse all sensor outputs. Then, an adaptive controller based on the sensor fusion output, a dynamic gain and a state observer is constructed to handle all the uncertainties caused by system nonlinearities, external disturbances, sensor failures and fusion mechanism. It is shown that by using the proposed scheme, the closed-loop system is stable, the sensor fusion mechanism can eliminate the effects of faulty sensors, and the real tracking error can be driven into a small compact set mainly affected by the fusion error. Experimental results are accomplished to validate the proposed scheme.
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一类基于传感器融合机制的非线性系统自适应输出反馈容错控制。
研究了一类具有系统非线性、传感器失效和外部干扰的非线性系统的输出反馈自适应容错跟踪控制,利用传感器冗余来提高系统的测量可靠性。首先设计了传感器融合机制和基于历史的加权平均算法来融合所有传感器输出。然后,基于传感器融合输出、动态增益和状态观测器构建自适应控制器,处理由系统非线性、外部干扰、传感器故障和融合机制引起的所有不确定性。仿真结果表明,采用该方案,闭环系统稳定,传感器融合机制能够消除故障传感器的影响,真实跟踪误差可以被驱动成一个主要受融合误差影响的小紧凑集。实验结果验证了该方案的有效性。
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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