International Journal of Control, Automation and Systems 2020; 18(5): 1128-1138
Published online December 26, 2019
https://doi.org/10.1007/s12555-019-0405-x
© The International Journal of Control, Automation, and Systems
In this paper, we consider the problem of predictor design for nonlinear systems in the presence of unknown time-varying input-delays. A cascade integral high-gain predictor is proposed to estimate the future state. With a distinctive structure, the predictor can handle unknown delays and eliminate the “peaking phenomenon” during the transient period. Then, a predictor-based output feedback control is designed to guarantee the boundedness of system states. Lyapunov-Krasovskii functional and perturbation theories are used to prove the convergence of the estimation error and the closed-loop system. Finally, simulation results illustrate the superior performance of the cascade integral predictor compared to the standard high-gain predictor.
Keywords High-gain predictors, nonlinear systems, output feedback, unknown time-varying delay.
International Journal of Control, Automation and Systems 2020; 18(5): 1128-1138
Published online May 1, 2020 https://doi.org/10.1007/s12555-019-0405-x
Copyright © The International Journal of Control, Automation, and Systems.
Kanghui He, Chaoyang Dong*, and Qing Wang
Beihang University
In this paper, we consider the problem of predictor design for nonlinear systems in the presence of unknown time-varying input-delays. A cascade integral high-gain predictor is proposed to estimate the future state. With a distinctive structure, the predictor can handle unknown delays and eliminate the “peaking phenomenon” during the transient period. Then, a predictor-based output feedback control is designed to guarantee the boundedness of system states. Lyapunov-Krasovskii functional and perturbation theories are used to prove the convergence of the estimation error and the closed-loop system. Finally, simulation results illustrate the superior performance of the cascade integral predictor compared to the standard high-gain predictor.
Keywords: High-gain predictors, nonlinear systems, output feedback, unknown time-varying delay.
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