Data-driven second-order iterative sliding mode control for cyber–physical systems under prescribed performance and DoS attacks

IF 3.3 2区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Yijie Yang , Dong Liu , Xin Wang , Zhujun Wang
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引用次数: 0

Abstract

This work investigates the second-order iterative sliding mode control problem of cyber–physical systems under prescribed performance and denial of service (DoS) attacks. An equivalent model of the controlled system is derived utilizing the dynamic linearization methodology, solely relying on process data. Through the novel tangent-type error transformation function, the confined error is equivalently transformed into the unconfined error. On this basis, a new second-order sliding function is devised to ensure that the error converges to the prearranged asymmetric region from the traditional time axis to the iteration axis. Based upon historical iterative data, an attack compensation mechanism is constructed to eliminate the negative impacts of attacks on the sensor. Finally, the effectiveness of the presented approach is validated via two examples.
规定性能和 DoS 攻击下网络物理系统的数据驱动二阶迭代滑动模式控制
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来源期刊
Journal of Process Control
Journal of Process Control 工程技术-工程:化工
CiteScore
7.00
自引率
11.90%
发文量
159
审稿时长
74 days
期刊介绍: This international journal covers the application of control theory, operations research, computer science and engineering principles to the solution of process control problems. In addition to the traditional chemical processing and manufacturing applications, the scope of process control problems involves a wide range of applications that includes energy processes, nano-technology, systems biology, bio-medical engineering, pharmaceutical processing technology, energy storage and conversion, smart grid, and data analytics among others. Papers on the theory in these areas will also be accepted provided the theoretical contribution is aimed at the application and the development of process control techniques. Topics covered include: • Control applications• Process monitoring• Plant-wide control• Process control systems• Control techniques and algorithms• Process modelling and simulation• Design methods Advanced design methods exclude well established and widely studied traditional design techniques such as PID tuning and its many variants. Applications in fields such as control of automotive engines, machinery and robotics are not deemed suitable unless a clear motivation for the relevance to process control is provided.
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