Finite‐time adaptive event‐triggered asynchronous state estimation for Markov jump systems with cyber‐attacks

Abstract

This article considers the issue of finite‐time asynchronous state estimation for event‐triggered nonlinear Markovian jump systems subject to cyber‐attacks. An adaptive event‐triggered scheme is introduced to cope with the capacity constraint of the networked resources. It is assumed that the transmitted sensor measurements may experience randomly malicious cyber‐attacks. Considering the effect of the adaptive event‐triggered scheme and the occurrence of cyber‐attacks, we establish a new state estimation error system model. Sufficient conditions of the finite‐time boundedness and the finite‐time boundedness are developed for the augmented system. Then, the design methods of the asynchronous estimator gains are derived, which can ensure the finite‐time boundedness of the estimation error system. Finally, a numerical example is given to show the effectiveness of the theoretical results.

Hidden Markov model‐based asynchronous exponential stabilization for stochastic Markovian jump systems with incomplete controller mode information

“…First, the definition is different. In this paper, we use the transition rates to describe the relationship between the system modes and controller modes (behaving in () and ()), while in [1, 25–31], conditional probability was used, that is, $$$ \mathcal{P}\left\{r(t)=i|\psi (t)=k\right\}={\sigma}_{ik} $$$. Second, we assume the transition rates of both the system and controller to be partly bounded known, while the detection probability $$$ {\sigma}_{ik} $$$ was usually assumed to be exactly known.…”

“…Remark A hidden Markov model is used to govern the controller switching. Unlike the existing results proposed in [1, 25–31], a new relationship between the system modes and controller modes is established, behaving on the transition rates. Note that in [1, 25–31], the detection probabilities had to be exactly known; however, the transition rates can be partly bounded known.…”

Tracking control for networked control systems with DoS attacks via reinforcement learning method

“…At present, numerous solutions have been proposed to reduce the negative impact of malicious attacks and some important results have been reported. These existing works are mainly focused on denial-of-service (DoS) attacks and deception attacks [14][15][16][17][18]. DoS attacks try to block the interconnection of communication modules, which will cause data transmission failure or even let the system instability [19,20].…”

Outlier‐resistant quantized control for T‐S fuzzy systems under multi‐channel‐enabled round‐robin protocol and deception attacks

“…Besides of the constraint network-bandwidth in networked systems, the network security is another important issue worthy of attention. [20][21][22] The network openness and vulnerabilities make the networked system expose to malicious attacks, which interfere the integrity and authenticity of the transmitted data during transmission aiming to destroy the target system. With the hope of eliminating the negative impacts inducing by malicious attacks, several types of malicious attacks to networked systems have been studied in depth including denial-of-service (DoS) attacks [23][24][25] and deception attacks.…”

“…Besides of the constraint network‐bandwidth in networked systems, the network security is another important issue worthy of attention 20‐22 . The network openness and vulnerabilities make the networked system expose to malicious attacks, which interfere the integrity and authenticity of the transmitted data during transmission aiming to destroy the target system.…”