Neural Optimization Techniques for Noisy-Data Observer-Based Neuro-Adaptive Control for Strict-Feedback Control Systems: Addressing Tracking and Predefined Accuracy Constraints

Neural Optimization Techniques for Noisy-Data Observer-Based Neuro-Adaptive Control for Strict-Feedback Control Systems: Addressing Tracking and Predefined Accuracy Constraints

This research proposes a fractional-order adaptive neural control scheme using an optimized backstepping (OB) approach to address strict-feedback nonlinear systems with uncertain control directions and predefined performance requirements. The OB framework integrates both fractional-order virtual and...

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Bibliographic Details
Main Authors: Abdulaziz Garba Ahmad, Taher Alzahrani
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Fractal and Fractional
Subjects:
fuzzy adaptive neural network control
input saturation
adaptive decentralized control
Nussbaum-type function
fractional-order stochastic complex large-scale system
unidentified control directions
Online Access:https://www.mdpi.com/2504-3110/9/6/389
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