Sequential Predictors for Uncertain Euler–Lagrange Systems with Large Transmission Delays
نویسندگان
چکیده
This paper investigates the state prediction problems for uncertain Euler–Lagrange systems with large time delays during data transmissions. A set of sequential predictors is proposed to estimate actual real-time states by using delayed information measurements. The arbitrarily are handled applying adequate numbers serial sub-predictors. Meanwhile, novel structure each subsystem designed deal nonlinearities and unknown dynamics in systems. Then, predictor design extended case without velocity measurements updating first sub-predictor. Sufficient conditions gains, ensuring boundness errors, obtained through Lyapunov–Krasovskii functionals. effectiveness robustness uncertainties method verified comparative results simulations.
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ژورنال
عنوان ژورنال: Fractal and fractional
سال: 2023
ISSN: ['2504-3110']
DOI: https://doi.org/10.3390/fractalfract7030244