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Adaptive State-Quantized Control of Uncertain Lower-Triangular Nonlinear Systems with Input Delay

Author

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  • Sung Jin Yoo

    (School of Electrical and Electronics Engineering, Chung-Ang University, 84 Heukseok-Ro, Dongjak-Gu, Seoul 06974, Korea)

Abstract

In this paper, we investigate the adaptive state-quantized control problem of uncertain lower-triangular systems with input delay. It is assumed that all state variables are quantized for the feedback control design. The error transformation method using an auxiliary time-varying signal is presented to deal with the compensation problem of input delay. Based on the error surfaces with the auxiliary variable, a neural-network-based adaptive state-quantized control scheme is constructed with the design of the input delay compensator. Different from existing results in the literature, the proposed method exhibits the following features: (i) compensating for the input delay effect by using quantized states; and (ii) establishing the stability of the adaptive quantized feedback control system in the presence of input delay. Furthermore, the boundedness of all the signals in the closed-loop and the convergence of the tracking error are analyzed. The effectiveness of the developed control strategy is demonstrated through the simulation on a hydraulic servo system.

Suggested Citation

  • Sung Jin Yoo, 2021. "Adaptive State-Quantized Control of Uncertain Lower-Triangular Nonlinear Systems with Input Delay," Mathematics, MDPI, vol. 9(7), pages 1-14, April.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:7:p:763-:d:528447
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    References listed on IDEAS

    as
    1. Yun Ho Choi & Sung Jin Yoo, 2020. "Quantized-Feedback-Based Adaptive Event-Triggered Control of a Class of Uncertain Nonlinear Systems," Mathematics, MDPI, vol. 8(9), pages 1-19, September.
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