Title
Adaptive Neural Controller Design Scheme of Nonlinear Delayed Systems With Completely Unknown Nonlinearities and Non-Strict-Feedback Structure.
Abstract
This paper proposes a novel adaptive intelligent tracking controller design scheme for a type of nonlinear delayed systems with completely unknown nonlinearities and non-strict-feedback structure. In the backsteppping-based design architecture, the intelligent estimation technique is utilized to approximate the unknown nonlinear functions via neural networks, and Lyapunov-Krasovskii functionals are designed to deal with the unknown delay terms. The constructed adaptive intelligent controller guarantees the semi-global boundedness of the resulting closed-loop system and the system output eventually converges to a small neighborhood around the desired reference signal. In the end, the presented simulation results verify the effectiveness of the proposed design method.
Year
DOI
Venue
2018
10.1109/ACCESS.2018.2877798
IEEE ACCESS
Keywords
Field
DocType
Nonlinear delayed systems,non-strict-feedback structure,neural networks,adaptive intelligent control,backstepping
Control theory,Backstepping,Nonlinear system,Adaptive system,Computer science,Controller design,Control theory,Design methods,Neural network controller,Artificial neural network,Distributed computing
Journal
Volume
ISSN
Citations 
6
2169-3536
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Kun Jiang101.35
Ben Niu247829.91
Junqing Li346242.69
Pei-Yong Duan411.02
Jihua Wang519153.78
Dong Yang611618.09