Research On Reliable Control For Cyber-Physical Systems Under Data Injection Attack

Cyber-physical system is a system that combines physical space and information space by using computing,communication and control technologies.Its application range is very wide,such as smart power grid,intelligent transportation and environmental monitoring.Due to the development of information physical system relying on network communication and other technologies,its openness is relatively strong,followed by increasing security risks.During the transmission of the measurement data and control data of the information physical system,the attacker can attack the information physical system by monitoring and tampering with relevant data,steal the information of the system and destroy the normal operation process of the system.Once the system is damaged,the loss may have a bad impact on the national economy and people’s livelihood,so the security of information physical system has been widely concerned.This paper focuses on.In the first chapter,describes the purpose and significance of this research,the relevant overview and research status.In the second chapter,introduces some of the basics and some of the lemmas and definitions that will be used in the proof.In the third chapter,recent technological advances in communications and computation have spurred a broad interest in control law architectures involving the monitoring,coordination,integration,and operation of sensing,computing,and communication components that tightly interact with the physical processes that they control.These systems are known as cyber-physical systems and due to their use of open computation and communication platform architectures,controlled cyber-physical systems are vulnerable to adversarial attacks.In this technical note,we propose a novel adaptive control architecture for addressing security and safety in cyber-physical systems.Specifically,we develop an adaptive controller that guarantees uniform ultimate bounded of the closed-loop dynamical system in the face of adversarial sensor and actuator attacks that are time-varying and partial asymptotic stability when the sensor and actuator attacks are time-invariant.Finally,we provide a numerical example to illustrate the efficacy of the proposed adaptive control architecture.In the fourth chapter,this chapter addresses the problem of robust adaptive fault-tolerant tracking control for a class of linear systems with parameter uncertainty,external disturbance,and actuator faults including loss of effectiveness,outage,and stuck.According to theonline estimation information provided by adaptive mechanism,a fault-tolerant compensation controller is constructed for robust tracking of closed-loop reference model systems.Compared with the existing results,by introducing the closed loop reference model which provides the additional degree-of-freedom,the transient performance of the systems can be improved.It is shown that the signals of the resulting adaptive closed-loop systems are bounded and the tracking error converges to zero asymptotically.A simulation example is provided to verify the effectiveness of the proposed fault-tolerant design method.In the fifth chapter,this chart is concerned with dissipativity-based fuzzy integral sliding mode control(FISMC)of continuous-time Takagi-Sugeno(T-S)fuzzy systems with matched unmatched uncertainties and external disturbance.To better accommodate the characteristics of T-S fuzzy models,an appropriate integral-type fuzzy switching surface is put forward by taking the state-dependent input matrix into account,which is the key contribution of the paper.Based on the utilization of Lyapunov function and property of the transition matrix for unmatched uncertainties,sufficient conditions are presented to guarantee the asymptotic stability of corresponding sliding mode dynamics with a strictly dissipative performance.A FISMC law is synthesized to drive system trajectories onto the fuzzy switching surface despite matched unmatched uncertainties and external disturbance.A modified adaptive FISMC law is further designed for adapting the unknown upper bound of matched uncertainty.Two practical examples are provided to illustrate the effectiveness and advantages of developed FISMC scheme.At last,conclusions and further research directions are given in the sixth chapter.