Adaptive event‐triggered tracking control for nonlinear networked systems with dynamic quantization and deception attacks
The problem of adaptive event‐triggered security tracking controller design is studied for interval type‐2 (IT2) Takagi‐Sugeno (T‐S) fuzzy‐approximation‐based nonlinear networked systems with deception attacks, privacy protection, and dynamic quantization in this paper. To reduce the network burden,...
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Published in | International journal of robust and nonlinear control Vol. 34; no. 12; pp. 8311 - 8333 |
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Format | Journal Article |
Language | English |
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01.08.2024
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Abstract | The problem of adaptive event‐triggered security tracking controller design is studied for interval type‐2 (IT2) Takagi‐Sugeno (T‐S) fuzzy‐approximation‐based nonlinear networked systems with deception attacks, privacy protection, and dynamic quantization in this paper. To reduce the network burden, the adaptive event‐triggered schemes (AETSs) and dynamic quantization are introduced to reduce unnecessary transmission and the number of network packets, respectively. Under the framework of network security, a novel security co‐design scheme with the tracking controller, AETSs, and the quantizers is developed, in which the privacy protection of the reference model and the deception attacks of the controller are taken into consideration simultaneously. Sufficient conditions for the results system to be mean‐square asymptotically stable with a H∞$$ {H}_{\infty } $$ tracking performance are established. Finally, two practical simulation examples demonstrate the effectiveness and novelty of the proposed design strategy. |
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AbstractList | The problem of adaptive event‐triggered security tracking controller design is studied for interval type‐2 (IT2) Takagi‐Sugeno (T‐S) fuzzy‐approximation‐based nonlinear networked systems with deception attacks, privacy protection, and dynamic quantization in this paper. To reduce the network burden, the adaptive event‐triggered schemes (AETSs) and dynamic quantization are introduced to reduce unnecessary transmission and the number of network packets, respectively. Under the framework of network security, a novel security co‐design scheme with the tracking controller, AETSs, and the quantizers is developed, in which the privacy protection of the reference model and the deception attacks of the controller are taken into consideration simultaneously. Sufficient conditions for the results system to be mean‐square asymptotically stable with a tracking performance are established. Finally, two practical simulation examples demonstrate the effectiveness and novelty of the proposed design strategy. The problem of adaptive event‐triggered security tracking controller design is studied for interval type‐2 (IT2) Takagi‐Sugeno (T‐S) fuzzy‐approximation‐based nonlinear networked systems with deception attacks, privacy protection, and dynamic quantization in this paper. To reduce the network burden, the adaptive event‐triggered schemes (AETSs) and dynamic quantization are introduced to reduce unnecessary transmission and the number of network packets, respectively. Under the framework of network security, a novel security co‐design scheme with the tracking controller, AETSs, and the quantizers is developed, in which the privacy protection of the reference model and the deception attacks of the controller are taken into consideration simultaneously. Sufficient conditions for the results system to be mean‐square asymptotically stable with a H∞$$ {H}_{\infty } $$ tracking performance are established. Finally, two practical simulation examples demonstrate the effectiveness and novelty of the proposed design strategy. |
Author | Chang, Xiao‐Heng Liu, Xi‐Ming |
Author_xml | – sequence: 1 givenname: Xi‐Ming orcidid: 0009-0001-4212-3784 surname: Liu fullname: Liu, Xi‐Ming organization: Bohai University – sequence: 2 givenname: Xiao‐Heng orcidid: 0000-0002-6197-1623 surname: Chang fullname: Chang, Xiao‐Heng email: changxiaoheng@sina.com organization: Bohai University |
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References | 2023; 31 2023; 53 2023; 10 2021; 8 2021; 21 2022; 130 2023; 33 2017; 47 2021; 29 2000; 8 2022; 67 2016; 94 2020; 122 2008; 53 2017; 354 2021; 51 2022; 135 2015; 273 2020; 7 2022; 121 2023; 24 2023 2019; 64 2022 2020; 50 2017; 13 2019; 49 2016; 63 2022; 30 2022; 32 2007; 2 2020; 65 2014; 50 2022; 127 2018; 14 e_1_2_9_30_1 e_1_2_9_31_1 e_1_2_9_11_1 e_1_2_9_34_1 e_1_2_9_10_1 e_1_2_9_35_1 e_1_2_9_13_1 e_1_2_9_32_1 e_1_2_9_12_1 e_1_2_9_33_1 e_1_2_9_15_1 e_1_2_9_38_1 e_1_2_9_39_1 e_1_2_9_17_1 e_1_2_9_36_1 e_1_2_9_16_1 e_1_2_9_37_1 e_1_2_9_19_1 e_1_2_9_18_1 e_1_2_9_41_1 e_1_2_9_42_1 e_1_2_9_20_1 e_1_2_9_40_1 e_1_2_9_22_1 e_1_2_9_45_1 e_1_2_9_21_1 e_1_2_9_46_1 e_1_2_9_24_1 e_1_2_9_43_1 e_1_2_9_23_1 e_1_2_9_44_1 e_1_2_9_8_1 e_1_2_9_7_1 e_1_2_9_6_1 e_1_2_9_5_1 e_1_2_9_4_1 Sun HY (e_1_2_9_14_1) 2023 e_1_2_9_3_1 e_1_2_9_2_1 e_1_2_9_9_1 e_1_2_9_26_1 e_1_2_9_49_1 e_1_2_9_25_1 e_1_2_9_28_1 e_1_2_9_47_1 e_1_2_9_27_1 e_1_2_9_48_1 e_1_2_9_29_1 |
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Snippet | The problem of adaptive event‐triggered security tracking controller design is studied for interval type‐2 (IT2) Takagi‐Sugeno (T‐S) fuzzy‐approximation‐based... |
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SubjectTerms | adaptive event‐triggered schemes Co-design Control systems design Controllers Counters deception attacks dynamic quantization Effectiveness H-infinity control Nonlinear control nonlinear networked systems Nonlinear systems Packets (communication) Privacy Security security tracking control Tracking control |
Title | Adaptive event‐triggered tracking control for nonlinear networked systems with dynamic quantization and deception attacks |
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