Regular Papers

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

Cascade Integral Predictors and Feedback Control for Nonlinear Systems with Unknown Time-varying Input-delays

Kanghui He, Chaoyang Dong*, and Qing Wang

Beihang University

Abstract

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.

Article

Regular Papers

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.

Cascade Integral Predictors and Feedback Control for Nonlinear Systems with Unknown Time-varying Input-delays

Kanghui He, Chaoyang Dong*, and Qing Wang

Beihang University

Abstract

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.

IJCAS
July 2024

Vol. 22, No. 7, pp. 2055~2340

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