Command Filter-Based Adaptive Optimal Control of Uncertain Nonlinear Systems with Quantized Input

Wei Yang; Hak-Keung Lam; Guozeng Cui; Jinpeng Yu

doi:10.1109/TFUZZ.2023.3296761

Command Filter-Based Adaptive Optimal Control of Uncertain Nonlinear Systems with Quantized Input

Wei Yang, Hak-Keung Lam, Guozeng Cui, Jinpeng Yu

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9 Citations (Scopus)

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Abstract

The issue of optimal output feedback control of uncertain nonlinear systems with quantized input is considered in this work. The fuzzy logic system (FLS) is employed to approximate unknown nonlinearities and optimal cost. By incorporating the observer technique into command filtered backstepping control (CFBC) framework, the feedforward quantized control signal is designed. Then, the optimal feedback control signal for the constructed affine system is derived via single network adaptive dynamic programming (ADP). Finally, an optimal output feedback quantized control scheme is proposed. With the aid of adaptive compensating technique, the requirement for prior knowledge of quantization parameter is eliminated. The boundedness of all the signals in the closed-loop system (CLS) is proved, and the output of system can reach the reference trajectory. Comparative simulations are implemented to verify the effectiveness of the proposed control strategy.

Original language	English
Pages (from-to)	1-6
Number of pages	6
Journal	IEEE Transactions on Fuzzy Systems
Early online date	17 Jul 2023
DOIs	https://doi.org/10.1109/TFUZZ.2023.3296761
Publication status	Published - 1 Aug 2023

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Command Filter-Based Adaptive Optimal Control of Uncertain Nonlinear Systems with Quantized Input (Accepted Auhtor Manuscript)Accepted author manuscript, 1.5 MB

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title = "Command Filter-Based Adaptive Optimal Control of Uncertain Nonlinear Systems with Quantized Input",

abstract = "The issue of optimal output feedback control of uncertain nonlinear systems with quantized input is considered in this work. The fuzzy logic system (FLS) is employed to approximate unknown nonlinearities and optimal cost. By incorporating the observer technique into command filtered backstepping control (CFBC) framework, the feedforward quantized control signal is designed. Then, the optimal feedback control signal for the constructed affine system is derived via single network adaptive dynamic programming (ADP). Finally, an optimal output feedback quantized control scheme is proposed. With the aid of adaptive compensating technique, the requirement for prior knowledge of quantization parameter is eliminated. The boundedness of all the signals in the closed-loop system (CLS) is proved, and the output of system can reach the reference trajectory. Comparative simulations are implemented to verify the effectiveness of the proposed control strategy.",

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T1 - Command Filter-Based Adaptive Optimal Control of Uncertain Nonlinear Systems with Quantized Input

AU - Yang, Wei

AU - Lam, Hak-Keung

AU - Cui, Guozeng

AU - Yu, Jinpeng

N1 - Publisher Copyright: IEEE

PY - 2023/8/1

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N2 - The issue of optimal output feedback control of uncertain nonlinear systems with quantized input is considered in this work. The fuzzy logic system (FLS) is employed to approximate unknown nonlinearities and optimal cost. By incorporating the observer technique into command filtered backstepping control (CFBC) framework, the feedforward quantized control signal is designed. Then, the optimal feedback control signal for the constructed affine system is derived via single network adaptive dynamic programming (ADP). Finally, an optimal output feedback quantized control scheme is proposed. With the aid of adaptive compensating technique, the requirement for prior knowledge of quantization parameter is eliminated. The boundedness of all the signals in the closed-loop system (CLS) is proved, and the output of system can reach the reference trajectory. Comparative simulations are implemented to verify the effectiveness of the proposed control strategy.

AB - The issue of optimal output feedback control of uncertain nonlinear systems with quantized input is considered in this work. The fuzzy logic system (FLS) is employed to approximate unknown nonlinearities and optimal cost. By incorporating the observer technique into command filtered backstepping control (CFBC) framework, the feedforward quantized control signal is designed. Then, the optimal feedback control signal for the constructed affine system is derived via single network adaptive dynamic programming (ADP). Finally, an optimal output feedback quantized control scheme is proposed. With the aid of adaptive compensating technique, the requirement for prior knowledge of quantization parameter is eliminated. The boundedness of all the signals in the closed-loop system (CLS) is proved, and the output of system can reach the reference trajectory. Comparative simulations are implemented to verify the effectiveness of the proposed control strategy.

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Command Filter-Based Adaptive Optimal Control of Uncertain Nonlinear Systems with Quantized Input

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