Exponential Continuous Non-Parametric Neural Identifier With Predefined Convergence Velocity

doi:10.1109/JAS.2022.105650

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	Exponential Continuous Non-Parametric Neural Identifier With Predefined Convergence Velocity
	Mariana Ballesteros; Rita Q. Fuentes-Aguilar; Isaac Chairez
发表期刊	IEEE/CAA Journal of Automatica Sinica
ISSN	2329-9266
	2022
卷号	9 期号:6 页码:1049-1060
摘要	This paper addresses the design of an exponential function-based learning law for artificial neural networks (ANNs) with continuous dynamics. The ANN structure is used to obtain a non-parametric model of systems with uncertainties, which are described by a set of nonlinear ordinary differential equations. Two novel adaptive algorithms with predefined exponential convergence rate adjust the weights of the ANN. The first algorithm includes an adaptive gain depending on the identification error which accelerated the convergence of the weights and promotes a faster convergence between the states of the uncertain system and the trajectories of the neural identifier. The second approach uses a time-dependent sigmoidal gain that forces the convergence of the identification error to an invariant set characterized by an ellipsoid. The generalized volume of this ellipsoid depends on the upper bounds of uncertainties, perturbations and modeling errors. The application of the invariant ellipsoid method yields to obtain an algorithm to reduce the volume of the convergence region for the identification error. Both adaptive algorithms are derived from the application of a non-standard exponential dependent function and an associated controlled Lyapunov function. Numerical examples demonstrate the improvements enforced by the algorithms introduced in this study by comparing the convergence settings concerning classical schemes with non-exponential continuous learning methods. The proposed identifiers overcome the results of the classical identifier achieving a faster convergence to an invariant set of smaller dimensions.
关键词	Exponential Lyapunov functions learning laws non-parametric identifier predefined convergence rate
DOI	10.1109/JAS.2022.105650
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/47572
专题	学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Mariana Ballesteros,Rita Q. Fuentes-Aguilar,Isaac Chairez. Exponential Continuous Non-Parametric Neural Identifier With Predefined Convergence Velocity[J]. IEEE/CAA Journal of Automatica Sinica,2022,9(6):1049-1060.
APA	Mariana Ballesteros,Rita Q. Fuentes-Aguilar,&Isaac Chairez.(2022).Exponential Continuous Non-Parametric Neural Identifier With Predefined Convergence Velocity.IEEE/CAA Journal of Automatica Sinica,9(6),1049-1060.
MLA	Mariana Ballesteros,et al."Exponential Continuous Non-Parametric Neural Identifier With Predefined Convergence Velocity".IEEE/CAA Journal of Automatica Sinica 9.6(2022):1049-1060.

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