With the expanding applications of multiple unmanned systems in various fields,more and more research attention has been paid to their security.The aim is to enhance the anti-interference ability,ensure their reliabil...With the expanding applications of multiple unmanned systems in various fields,more and more research attention has been paid to their security.The aim is to enhance the anti-interference ability,ensure their reliability and stability,and better serve human society.This article conducts adaptive cooperative secure tracking consensus of networked multiple unmanned systems subjected to false data injection attacks.From a practical perspective,each unmanned system is modeled using high-order unknown nonlinear discrete-time systems.To reduce the communication bandwidth between agents,a quantizer-based codec mechanism is constructed.This quantizer uses a uniform logarithmic quantizer,combining the advantages of both quantizers.Because the transmission information attached to the false data can affect the accuracy of the decoder,a new adaptive law is added to the decoder to overcome this difficulty.A distributed controller is devised in the backstepping framework.Rigorous mathematical analysis shows that our proposed control algorithms ensure that all signals of the resultant systems remain bounded.Finally,simulation examples reveal the practical utility of the theoretical analysis.展开更多
This paper develops an event-triggered resilient consensus control method for the nonlinear multiple unmanned systems with a data-based autoregressive integrated moving average(ARIMA)agent state prediction mechanism a...This paper develops an event-triggered resilient consensus control method for the nonlinear multiple unmanned systems with a data-based autoregressive integrated moving average(ARIMA)agent state prediction mechanism against periodic denial-of-service(Do S)attacks.The state predictor is used to predict the state of neighbor agents during periodic Do S attacks and maintain consistent control of multiple unmanned systems under Do S attacks.Considering the existing prediction error between the actual state and the predicted state,the estimated error is regarded as the uncertainty system disturbance,which is dealt with by the designed disturbance observer.The estimated result is used in the design of the consistent controller to compensate for the system uncertainty error term.Furthermore,this paper investigates dynamic event-triggered consensus controllers to improve resilience and consensus under periodic Do S attacks and reduce the frequency of actuator output changes.It is proved that the Zeno behavior can be excluded.Finally,the resilience and consensus capability of the proposed controller and the superiority of introducing a state predictor are demonstrated through numerical simulations.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant U20B2073,Grant 62103047Beijing Institute of Technology Research Fund Program for Young ScholarsYoung Elite Scientists Sponsorship Program by BAST(Grant No.BYESS2023365)
文摘With the expanding applications of multiple unmanned systems in various fields,more and more research attention has been paid to their security.The aim is to enhance the anti-interference ability,ensure their reliability and stability,and better serve human society.This article conducts adaptive cooperative secure tracking consensus of networked multiple unmanned systems subjected to false data injection attacks.From a practical perspective,each unmanned system is modeled using high-order unknown nonlinear discrete-time systems.To reduce the communication bandwidth between agents,a quantizer-based codec mechanism is constructed.This quantizer uses a uniform logarithmic quantizer,combining the advantages of both quantizers.Because the transmission information attached to the false data can affect the accuracy of the decoder,a new adaptive law is added to the decoder to overcome this difficulty.A distributed controller is devised in the backstepping framework.Rigorous mathematical analysis shows that our proposed control algorithms ensure that all signals of the resultant systems remain bounded.Finally,simulation examples reveal the practical utility of the theoretical analysis.
基金supported by the National Natural Science Foundation of China(Nos.61833013,62003162,62233009)Natural Science Foundation of Jiangsu Province of China(Nos.BK20200416,BK20222012)+5 种基金China Postdoctoral Science Foundation(Nos.2020TQ0151,2020M681590)Fundamental Research Funds for the Central Universities(No.NS2021025)Industry-University Research Innovation Foundation for the Chinese Ministry of Education(No.2021ZYA02005)Science and Technology on Space Intelligent Control Laboratory(No.HTKJ2022KL502015)Aeronautical Science Foundation of China(No.20200007018001)Natural Sciences and Engineering Research Council of Canada
文摘This paper develops an event-triggered resilient consensus control method for the nonlinear multiple unmanned systems with a data-based autoregressive integrated moving average(ARIMA)agent state prediction mechanism against periodic denial-of-service(Do S)attacks.The state predictor is used to predict the state of neighbor agents during periodic Do S attacks and maintain consistent control of multiple unmanned systems under Do S attacks.Considering the existing prediction error between the actual state and the predicted state,the estimated error is regarded as the uncertainty system disturbance,which is dealt with by the designed disturbance observer.The estimated result is used in the design of the consistent controller to compensate for the system uncertainty error term.Furthermore,this paper investigates dynamic event-triggered consensus controllers to improve resilience and consensus under periodic Do S attacks and reduce the frequency of actuator output changes.It is proved that the Zeno behavior can be excluded.Finally,the resilience and consensus capability of the proposed controller and the superiority of introducing a state predictor are demonstrated through numerical simulations.