FSE-RBFNN-Based AILC of Finite Time Complete Tracking for a Class of Time-Varying NPNL Systems with Initial State Errors

FSE-RBFNN-Based AILC of Finite Time Complete Tracking for a Class of Time-Varying NPNL Systems with Initial State Errors

The paper proposed an adaptive iterative learning control (AILC) strategy for the unmatched uncertain time-varying nonparameterized nonlinear systems (NPNL systems). Addressing the difficulty of nonlinear parameterization terms in system models, a new function approximator (FSE-RBFNN) which is combi...

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Bibliographic Details
Main Authors: Chunli Zhang, Lei Yan, Yangjie Gao
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:Advances in Mathematical Physics
Online Access:http://dx.doi.org/10.1155/2024/3744735
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