NDLI: Adaptive neural network control of uncertain MIMO nonlinear systems with input saturation

Content Provider	Springer Nature Link
Author	Zhou, Shengfeng Chen, Mou Ong, Chong Jin Chen, Peter C. Y.
Copyright Year	2015
Abstract	In this paper, an adaptive neural network (NN) tracking controller is developed for a class of uncertain multi-input multi-output (MIMO) nonlinear systems with input saturation. Radial basis function neural networks are utilized to approximate the unknown nonlinear functions in the MIMO system. A novel auxiliary system is developed to compensate the effects induced by input saturation (in both magnitude and rate) during tracking control. Endowed with a switching structure that integrates two existing representative auxiliary system designs, this novel auxiliary system improves control performance by preserving their advantages. It provides a comprehensive design structure in which parameters can be adjusted to meet the required control performance. The auxiliary system signal is utilized in both the control law and the neural network weight-update laws. The performance of the resultant closed-loop system is analyzed, and the bound of the transient error is established. Numerical simulations are presented to demonstrate the effectiveness of the proposed adaptive neural network control.
Starting Page	1317
Ending Page	1325
Page Count	9
File Format	PDF
ISSN	09410643
Journal	Neural Computing and Applications
Volume Number	27
Issue Number	5
e-ISSN	14333058
Language	English
Publisher	Springer London
Publisher Date	2015-06-23
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Neural networks (NNs) Input saturation MIMO systems Adaptive tracking control Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Probability and Statistics in Computer Science Computational Science and Engineering Image Processing and Computer Vision Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

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