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Yang, Guichao; Yao, Jianyong

Multilayer neurocontrol of high-order uncertain nonlinear systems with active disturbance rejection. (English) Zbl 1533.93413

Int. J. Robust Nonlinear Control 34, No. 4, 2972-2987 (2024).
Summary: Multilayer neural networks can approximate endogenous disturbances with relatively high accuracy. However, for multilayer-neural-network-based control methods of high-order uncertain nonlinear systems, hard to handle large exogenous disturbances especially for mismatched types, complex controller scheme and so on, make them difficult to be practical. Therefore, a novel high-performance multilayer neurocontroller which can simultaneously reject matched and mismatched disturbances will be proposed in this paper. Specially, strong endogenous and exogenous disturbances will be feedforwardly compensated. Additionally, the proposed controller not only protects from “explosion of complexity”, but also owns a simple scheme.
© 2024 John Wiley & Sons Ltd.

MSC:

93C41 Control/observation systems with incomplete information
93C10 Nonlinear systems in control theory
93C73 Perturbations in control/observation systems
68T07 Artificial neural networks and deep learning

Keywords:

active disturbance rejection; command filtered backstepping; extended state observer; multilayer neural networks; multilayer neuroadaptive disturbance observer; nonlinear system
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References:

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