Affine Transformed IT2 Fuzzy Event-Triggered Control Under Deception Attacks

[1]  Bugong Xu,et al.  Adaptive event-triggered H∞ fuzzy filtering for interval type-2 T-S fuzzy-model-based networked control systems with asynchronously and imperfectly matched membership functions , 2019, J. Frankl. Inst..

[2]  Soummya Kar,et al.  Dynamic Attack Detection in Cyber-Physical Systems With Side Initial State Information , 2015, IEEE Transactions on Automatic Control.

[3]  Oscar Castillo,et al.  A generalized type-2 fuzzy logic approach for dynamic parameter adaptation in bee colony optimization applied to fuzzy controller design , 2017, Inf. Sci..

[4]  Dong Yue,et al.  Distributed event‐triggered state estimators design for sensor networked systems with deception attacks , 2019, IET Control Theory & Applications.

[5]  Hong Lin,et al.  Distributed event-triggered control for networked control systems with stochastic cyber-attacks , 2019, J. Frankl. Inst..

[6]  Uthman A. Baroudi,et al.  Modeling and control of Cyber-Physical Systems subject to cyber attacks: A survey of recent advances and challenges , 2019, Neurocomputing.

[7]  Peng Shi,et al.  Event-Triggered Fault Detection Filter Design for a Continuous-Time Networked Control System , 2016, IEEE Transactions on Cybernetics.

[8]  Sung Hyun Kim,et al.  Dissipative control of interval type-2 nonhomogeneous Markovian jump fuzzy systems with incomplete transition descriptions , 2020 .

[9]  Frédéric Gouaisbaut,et al.  Wirtinger-based integral inequality: Application to time-delay systems , 2013, Autom..

[10]  Yongsik Jin,et al.  Development of Autonomous Driving Systems Using State Estimator with Multi-rate Sampled-data , 2019, 2019 IEEE International Conference on Consumer Electronics (ICCE).

[11]  Tao Zhang,et al.  Event-triggered filter design for nonlinear cyber-physical systems subject to deception attacks. , 2020, ISA transactions.

[12]  Yugang Niu,et al.  Input-to-State Stabilization of Interval Type-2 Fuzzy Systems Subject to Cyberattacks: An Observer-Based Adaptive Sliding Mode Approach , 2020, IEEE Transactions on Fuzzy Systems.

[13]  B. B. Zaidan,et al.  Survey on fuzzy TOPSIS state-of-the-art between 2007 and 2017 , 2019, Comput. Oper. Res..

[14]  Roman Obermaisser,et al.  Event-Triggered and Time-Triggered Control Paradigms , 2004, Real-Time Systems Series.

[15]  Juan R. Castro,et al.  A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems , 2016, Inf. Sci..

[16]  Sangmoon Lee,et al.  Novel Stabilization Criteria for T–S Fuzzy Systems With Affine Matched Membership Functions , 2019, IEEE Transactions on Fuzzy Systems.

[17]  Jerry M. Mendel,et al.  Interval Type-2 Fuzzy Logic Systems Made Simple , 2006, IEEE Transactions on Fuzzy Systems.

[18]  Yan Shi,et al.  Fuzzy adaptive control of a class of nonlinear systems with unmodeled dynamics , 2019, International Journal of Adaptive Control and Signal Processing.

[19]  Jian Xiao,et al.  Observer-based H∞ controller design for interval type-2 T-S fuzzy systems , 2016, Neurocomputing.

[20]  Wookyong Kwon,et al.  Integral-based event-triggered synchronization criteria for chaotic Lur’e systems with networked PD control , 2018, Nonlinear Dynamics.

[21]  Qing-Long Han,et al.  Security Control for Discrete-Time Stochastic Nonlinear Systems Subject to Deception Attacks , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[22]  Jinde Cao,et al.  Nonstationary Control for T–S Fuzzy Markovian Switching Systems With Variable Quantization Density , 2020, IEEE Transactions on Fuzzy Systems.

[23]  Fuad E. Alsaadi,et al.  Security‐guaranteed filtering for discrete‐time stochastic delayed systems with randomly occurring sensor saturations and deception attacks , 2017 .

[24]  Ju H. Park,et al.  New results for sampled-data control of interval type-2 fuzzy nonlinear systems , 2020, J. Frankl. Inst..

[25]  Hak-Keung Lam,et al.  Observer-Based Fault Detection for Nonlinear Systems With Sensor Fault and Limited Communication Capacity , 2016, IEEE Transactions on Automatic Control.

[26]  Qing-Long Han,et al.  State Estimation for Static Neural Networks With Time-Varying Delays Based on an Improved Reciprocally Convex Inequality , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[27]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[28]  Jan Lunze,et al.  A state-feedback approach to event-based control , 2010, Autom..

[29]  Dong Yue,et al.  A Delay System Method for Designing Event-Triggered Controllers of Networked Control Systems , 2013, IEEE Transactions on Automatic Control.

[30]  Florian Dörfler,et al.  Attack Detection and Identification in Cyber-Physical Systems -- Part II: Centralized and Distributed Monitor Design , 2012, ArXiv.

[31]  Yan Shi,et al.  Neural Networks-Based Distributed Adaptive Control of Nonlinear Multiagent Systems , 2020, IEEE Transactions on Neural Networks and Learning Systems.

[32]  Junwu Zhu,et al.  Adaptive consensus control of leader-following systems with transmission nonlinearities , 2019, Int. J. Control.

[33]  Yang Xiang,et al.  A survey on security control and attack detection for industrial cyber-physical systems , 2018, Neurocomputing.

[34]  Hamid Reza Karimi,et al.  Quantized Nonstationary Filtering of Networked Markov Switching RSNSs: A Multiple Hierarchical Structure Strategy , 2020, IEEE Transactions on Automatic Control.

[35]  Guangtao Ran,et al.  Novel mixed-triggered filter design for interval type-2 fuzzy nonlinear Markovian jump systems with randomly occurring packet dropouts , 2019, Nonlinear Dynamics.

[36]  Weiyi Liu,et al.  Security analysis for Cyber-Physical Systems against stealthy deception attacks , 2013, 2013 American Control Conference.