2021 60th IEEE Conference on Decision and Control (CDC) 2021
DOI: 10.1109/cdc45484.2021.9683393
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Finite-time Identification of Unknown Discrete-time Nonlinear Systems Using Concurrent Learning

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Cited by 6 publications
(1 citation statement)
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“…While most real-world systems are CT in nature, DT systems are of great importance since systems are typically discretized and controlled with digital computers and micro-controllers in real-world applications. Even though finite-time stability of DT is studied in [15], [16], [35], [36], fixed-time stability of DT systems is surprisingly unsettled, despite its practical importance. This gap motivates us to present fixed-time Lyapunov stability conditions that pave the way for realization of fixed-time control and identification of DT systems through designing appropriate controllers and adaptation laws, respectively.…”
Section: Introductionmentioning
confidence: 99%
“…While most real-world systems are CT in nature, DT systems are of great importance since systems are typically discretized and controlled with digital computers and micro-controllers in real-world applications. Even though finite-time stability of DT is studied in [15], [16], [35], [36], fixed-time stability of DT systems is surprisingly unsettled, despite its practical importance. This gap motivates us to present fixed-time Lyapunov stability conditions that pave the way for realization of fixed-time control and identification of DT systems through designing appropriate controllers and adaptation laws, respectively.…”
Section: Introductionmentioning
confidence: 99%