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• W4362656654 endingPage "110995" @default.
• W4362656654 startingPage "110995" @default.
• W4362656654 abstract "There is a growing interest in differentiation algorithms that converge in fixed time with a predefined Upper Bound on the Settling Time (UBST). However, existing differentiation algorithms are limited to signals having an $n$-th order Lipschitz derivative. Here, we introduce a general methodology based on time-varying gains to circumvent this limitation, allowing us to design $n$-th order differentiators with a predefined UBST for the broader class of signals whose $(n+1)$-th derivative is bounded by a function with bounded logarithmic derivative. Unlike existing methods whose time-varying gain tends to infinity, our approach yields a time-varying gain that remains bounded at convergence time. We show how this last property maintains exact convergence using bounded gains when considering a compact set of initial conditions and improves the algorithm's performance to measurement noise." @default.
• W4362656654 created "2023-04-07" @default.
• W4362656654 creator A5010534287 @default.
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• W4362656654 date "2023-07-01" @default.
• W4362656654 modified "2023-10-03" @default.
• W4362656654 title "An arbitrary-order exact differentiator with predefined convergence time bound for signals with exponential growth bound" @default.
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• W4362656654 doi "https://doi.org/10.1016/j.automatica.2023.110995" @default.
• W4362656654 hasPublicationYear "2023" @default.
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