SMC for Discrete-Time Networked Semi-Markovian Switching Systems With Random DoS Attacks and Applications

Abstract

This article concentrates on the discrete-time sliding mode control (DTSMC) problem for uncertain networked semi-Markovian switching systems (S-MSSs) under random denialof-service (DoS) attacks. The semi-Markovian kernel (SMK) approach is utilized such that the switching among different modes is mutually governed by the transition probability and the sojourn-time distribution function. Considering randomly occurring DoS attacks, a sliding mode function related to the attack probability is constructed to analyze the impact of malicious attacks. Then, sufficient conditions under the equivalent DTSMC law are derived in view of the σ -error mean square stability criterion. Furthermore, the synthesis problem of the proposed DTSMC law ensures that the resulting closed-loop system dynamics can be driven onto the prespecified sliding region within a limited time. Finally, an electronic throttle control system is shown to validate the proposed algorithm.

Nussbaum gain adaptive control for full‐state constrained cyber‐physical system under network attacks and actuator failures

“…where 𝛼 i−1 is the virtual controller to be designed. z i = 𝜇 ⌣ z i can be obtained from (9). By using the time-varying BLF defined below, an adaptive security control scheme is proposed.…”

“…Accurate identification of attack types is crucial to system security. At present, denial of service attacks (DOSA), 9‐11 replay attacks, 12‐14 eavesdropping attacks, 15‐17 and FDIA (false data injection attacks) 18‐20 are the main types of common network attacks. DOSA is a depleting attack on the resources of the attacked object, which interrupts the normal communication of the system.…”

“…The main contributions of this article can be summarized as follows Compared with the existing results 31 that the attack gain must be positive, this article considers that the attack gain caused by FDIA is unknown. The Nussbaum function is used to deal with the unknown attack gain, which reduces the impact of the attack on the sensor network. Different from the recent research on CPS 18,19 which is limited to the FDIA problem, in the control design process, not only the FDIA is considered, but also the time‐varying BLFs are used to constrain the system states, and a new adaptive security control scheme is constructed. Based on the problem of FDIA destroying sensor networks is considered in References 21 and 32, we also consider the problem of actuator faults, including failure, and bias faults. The adaptive law is designed in the backstepping process to eliminate the influence of actuator faults and enhance the robustness of the attacked CPS. …”

Sliding mode control for Markovian jump systems under a switched scheduling protocol

“…Many methods have been presented to address these phenomena, for example, dissipative control, 18 $$$ {H}_{\infty } $$$ control, 19 sliding mode control (SMC) 20–23 and so on. Among them, SMC has shown significant advantages such as insensitivity to external matching disturbances and parameter uncertainties, and has been effectively designed for networked control systems, for example, packet dropouts, 24 cyber attacks, 25,26 delays, 27 fading channel 28 and so forth.…”

Containment control of networked heterogeneous autonomous surface vehicles: A data‐driven control approach

“…Recently, autonomous surface vehicles (ASVs) have been conspicuously investigated and the correspondingly coordinated control of ASVs has attracted increasingly attention from both engineering community and research group. [1][2][3][4][5] Generally, by virtue of the advantages of networked control techniques, [6][7][8][9] the coordinated control can enable multiple ASVs to work together to achieve a collective goal while with salient superiorities, including strong flexibility, high reliability, low cost and powerful regulation ability in completing various complex space tasks. As result, the coordinated control has been widely used in various fields, for example, sensor networks, rescue, reconnaissance operations and so forth.…”