Adaptive Neural Controller Design Scheme of Nonlinear Delayed Systems With Completely Unknown Nonlinearities and Non-Strict-Feedback Structure
Author(s) -
Kun Jiang,
Ben Niu,
Jun-Qing Li,
Peiyong Duan,
Jihua Wang,
Dong Yang
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2877798
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
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.
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