文献类型：期刊文献

英文题名：Adaptive Neural Sliding Mode Control for Singular Semi-Markovian Jump Systems Against Actuator Attacks

作者：Cao, Zhiru[1];Niu, Yugang[1];Zou, Yuanyuan[2]

机构：[1]East China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China

年份：2021

卷号：51

期号：3

起止页码：1523

外文期刊名：IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS

收录：;EI(收录号：20210809967515);WOS:【SCI-EXPANDED(收录号:WOS:000619380900014)】；

基金：This work was supported in part by the National Natural Science Foundation of China from China under Grant 61673174 and Grant 61773162, and in part by the 111 Project from China under Grant B17017.

语种：英文

外文关键词：Actuators; Observers; Adaptive systems; Neural networks; Optimization; Symmetric matrices; Actuator attacks; adaptive sliding mode control (SMC); neural network; singular semi-Markovian jump systems (S-MJSs)

摘要：The adaptive sliding mode control (SMC) problem is addressed for singular semi-Markovian jump systems (S-MJSs) against actuator attacks, in which the transition rates rely on the random sojourn time and are not constant, and the system states are unavailable. Moreover, the vulnerability of control signals transmitted via communication network means that the actuators may receive the attacked control signals. For the sake of reducing the effect of actuator attacks, the neural network technique is used to approximate the false information injected by adversaries. Meanwhile, a sliding mode observer is introduced to estimate the unmeasured states. An adaptive SMC law is proposed to guarantee that the estimation states and errors can reach to the sliding surfaces, and the stochastic admissibility of the singular S-MJSs can be ensured. In the end, an example is applied to illustrate the method in this paper.