Investigations On Some Problems Of Security Control For Event-driven T-S Fuzzy Systems

Takagi-Sugeno(T-S)fuzzy systems can approximate any nonlinear systems,which have been an vital tool of analyzing and modeling nonlinear systems in the researches of control theory.In the networked T-S fuzzy systems,data are transmitted through communication network.The rapid development of computer network brings many conveniences to information transmission,however,the network is vulnerable to malicious signal attacks due to its openness,including deception attacks and denial-of-service(Do S)attacks.In order to mitigate the communication pressure,the event-triggered scheme and quantization mechanism are adopted to relieve the effects of limited communication resources.As one of the improved event-triggered scheme,the adaptive event-triggered mechanism can adaptively adjust event-triggering condition while preserving the system performance,which can further decrease the amount of redundant data.Besides,the behavior of saturation usually has an impact on system performance owing to the restrictions of physical equipment or technological means.Based on the above analysis,the main contents of this paper are summarized as follows:(1)For the T-S fuzzy neural networks,event-triggered scheme is utilized to relief the network transmission pressure.By taking the influence of the deception attacks into consideration,a mathematical model for the T-S fuzzy neural networks with event-triggered scheme is established.By the use of Lyapunov stability theory and linear matrix inequalities(LMIs)techniques,the sufficient conditions to ensure the stability of the systems are derived,the gains of the state estimator are acquired in the form of LMIs.Finally,a simulated example is presented to illustrate the effectiveness of the proposed method.(2)In the cyber-physical systems approximated by T-S fuzzy systems,the event-triggered scheme and quantization mechanism are applied to relieve the effects brought by limited communication resources.Then by considering sensor saturation and Do S attacks,a novel model of estimating error system is constructed.By using the Lyapunov stability theory,the sufficient conditions to ensure the system exponentially stable are derived,and the co-design of the estimator gains and the event-triggered parameters is realized.At last,a simulated example is provided for illustrating the feasibility of the proposed method.(3)For the networked control systems described by T-S fuzzy systems,a multiple cyber-attacks model is firstly established by considering deception attacks and Do S attacks at the same time.An adaptive event-triggered mechanism is introduced to relieve the network load.Then a novel mathematical model for T-S fuzzy systems with multiple cyber-attacks and adaptive event-triggered mechanism is proposed.Based on the built model,sufficient conditions to guarantee the exponentially mean square stability of system are achieved by utilizing Lyapunov stability theory.Moreover,the controller gains are derived with the help of LMI technique.Lastly,a simulated example with mass-spring system is presented for illustrating the effectiveness of the proposed method.The advantage of adaptive event triggering mechanism is verified by a comparative experiment.