Stabilization of Networked Control Systems Under DoS Attacks and Output Quantization
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Publication:5125778
DOI10.1109/TAC.2019.2949096OpenAlexW2982097845MaRDI QIDQ5125778
Ahmet Cetinkaya, Hideaki Ishii, Masashi Wakaiki
Publication date: 7 October 2020
Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1709.08149
Related Items (17)
Stabilization of networked singular control systems under double-channel quantization and DoS attacks ⋮ Observer-based synchronization of memristive neural networks under DoS attacks and actuator saturation and its application to image encryption ⋮ Quantized MPSC for switched systems based on permissible type-switching mechanism ⋮ Quantized stabilization of switched systems with partly unstabilizable subsystems and denial‐of‐service attacks ⋮ Self-triggered resilient stabilization of linear systems with quantized outputs ⋮ Quantized control for networked switched systems under denial-of-service attacks via a barrier event-triggered mechanism ⋮ Observer-based event-triggered non-PDC control for networked T-S fuzzy systems under actuator failures and aperiodic DoS attacks ⋮ Dynamic event-triggered output feedback control for networked Markovian jump systems under hybrid attacks ⋮ Resilient quantized control for asynchronous sampled-data networked control systems under DoS attacks ⋮ MPSC for networked switched systems based on timing-response event-triggering scheme ⋮ The bottleneck and ceiling effects in quantized tracking control of heterogeneous multi-agent systems under DoS attacks ⋮ Resilient control for networked control systems with dynamic quantization and DoS attacks ⋮ Encryption–decryption‐based event‐triggered consensus control for nonlinear MASs under DoS attacks ⋮ Finite-time control for discrete-time nonlinear Markov switching LPV systems with DoS attacks ⋮ Quantized output feedback control for switched systems with DoS attacks and event-triggered sampling ⋮ Quantized state feedback stabilization of nonlinear systems under denial-of-service ⋮ Quantisation compensated data-driven iterative learning control for nonlinear systems
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