多故障随机非线性系统的事件触发自适应补偿控制:一种改进的切换阈值策略。

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Yang Du , Shan-Liang Zhu , Yu-Qun Han
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引用次数: 0

摘要

研究一类具有有限执行器失效和系统外部突然失效的随机非线性系统的事件触发自适应容错控制问题。与现有的事件触发机制(etm)不同,本文提出了一种改进的切换阈值机制(STM),该机制有效地解决了当控制器的幅值大小及其变化率过大时,由于大信号脉冲所带来的系统安全隐患,同时还节省了能耗。特别是在执行器故障和系统外部故障同时发生可能导致控制器过换率的情况下,利用多维泰勒网络(MTN)逼近技术,基于改进STM设计的自适应容错控制方案不仅降低了资源消耗,而且通过保证系统安全运行,间接提高了系统的控制性能。通过所提出的控制方案,不仅保证了闭环系统的所有信号在概率上有界,而且跟踪误差收敛。动态模型仿真验证了该方案的可行性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Event-triggered adaptive compensation control for stochastic nonlinear systems with multiple failures: An improved switching threshold strategy
This paper considers the event-triggered adaptive fault-tolerant control (FTC) problem for a class of stochastic nonlinear systems suffering from finite number of actuator failures and abrupt system external failure. Unlike existing event-triggered mechanisms (ETMs), this paper proposes an improved switching threshold mechanism (STM) that effectively addresses the potential system security hazards caused by large signal impulses when both the magnitude size of the controller and its rate of change are too large, while also saving energy consumption. Especially, when the occurrence of both actuator failure and system external failure may lead to over-change rate of the controller, by using the multi-dimensional Taylor network (MTN) approximation technique, the adaptive fault-tolerant control scheme designed based on the improved STM not only has lower resource consumption, but also indirectly improves the control performance of the system by ensuring the system security operation. Not only does it ensure that all signals of the closed-loop system are bounded in probability and the tracking error converges through the proposed control scheme. The feasibility and superiority of the developed scheme is well shown by dynamic model simulations.
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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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