Finite-time adaptive dynamic surface control for output feedback nonlinear systems with unmodeled dynamics and quantized input delays

Changgui Wu; Liang Zhao; Changgui Wu; Liang Zhao

doi:10.3934/math.20241518

AIMS Mathematics

2024, Volume 9, Issue 11: 31553-31580. doi: 10.3934/math.20241518

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Research article

Finite-time adaptive dynamic surface control for output feedback nonlinear systems with unmodeled dynamics and quantized input delays

Changgui Wu ^{1
,
,},
Liang Zhao ²

1.
The City Vocational College of Jiangsu (Nantong), Nantong City, Jiangsu Province, 226006, China
2.
School of Information Science and Technology, Fudan University, Shanghai, 201203, China

Received: 11 July 2024 Revised: 09 September 2024 Accepted: 24 September 2024 Published: 06 November 2024
MSC : 93A30, 93C10, 97N40

We delved into a category of output feedback nonlinear systems that are distinguished by unmodeled dynamics, quantized input delays, and dynamic uncertainties. We introduce a novel finite-time adaptive dynamic surface control scheme developed through the construction of a first-order nonlinear filter. This approach integrates Young's inequality with neural network technologies. Then, to address unmodeled dynamics, the scheme incorporates a dynamic signal and utilizes Radial Basis Function (RBF) neural networks to approximate unknown smooth functions. Furthermore, an auxiliary function is devised to mitigate the impact of input quantization delays on the system's performance. The new controller design is both simple and effective, addressing the "hasingularity" problems typically associated with traditional finite-time controls. Theoretical analyses and simulation outcomes confirm the effectiveness of this approach, guaranteeing that all signals in the system are confined within a finite period.
- unmodeled dynamics,
- quantized input time delay,
- first-order nonlinear filter,
- finite time stability,
- dynamic surface control
Citation: Changgui Wu, Liang Zhao. Finite-time adaptive dynamic surface control for output feedback nonlinear systems with unmodeled dynamics and quantized input delays[J]. AIMS Mathematics, 2024, 9(11): 31553-31580. doi: 10.3934/math.20241518

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Abstract

We delved into a category of output feedback nonlinear systems that are distinguished by unmodeled dynamics, quantized input delays, and dynamic uncertainties. We introduce a novel finite-time adaptive dynamic surface control scheme developed through the construction of a first-order nonlinear filter. This approach integrates Young's inequality with neural network technologies. Then, to address unmodeled dynamics, the scheme incorporates a dynamic signal and utilizes Radial Basis Function (RBF) neural networks to approximate unknown smooth functions. Furthermore, an auxiliary function is devised to mitigate the impact of input quantization delays on the system's performance. The new controller design is both simple and effective, addressing the "hasingularity" problems typically associated with traditional finite-time controls. Theoretical analyses and simulation outcomes confirm the effectiveness of this approach, guaranteeing that all signals in the system are confined within a finite period.

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