Intelligence computation based on adaptive tracking design for a class of non-linear discrete-time systems

In this article, a direct adaptive neural networks control algorithm is presented for a class of SISO discrete-time systems with non-symmetric dead-zone. The property of the dead-zone is discretized. Mean value theorem is used to transform the systems into a special form. The unknown functions in th...

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Bibliographic Details
Published in:Neural computing & applications Vol. 23; no. 5; pp. 1351 - 1357
Main Authors: Liu, Lei, Liu, Yan-Jun, Li, Dong-Juan
Format: Journal Article
Language:English
Published: London Springer London 01.10.2013
Springer
Subjects:
Applied sciences
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Computer science; control theory; systems
Connectionism. Neural networks
Data Mining and Knowledge Discovery
Exact sciences and technology
Image Processing and Computer Vision
Original Article
Probability and Statistics in Computer Science
Non-symmetric dead-zone
The neural networks
Non-linear systems
Adaptive control
Tracking
Adaptive algorithm
Intelligence
Use value
Lyapunov method
Linear time
Adaptive method
Uncertain system
Efficiency
Tracking error
Input output model
Closed loop
Dead zone
Neural network
Mean value
Radial basis function
Symmetric matrix
Discrete time
Distributed control
SISO system
Directed graph
ISSN:0941-0643, 1433-3058
Online Access:Get full text
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Summary:In this article, a direct adaptive neural networks control algorithm is presented for a class of SISO discrete-time systems with non-symmetric dead-zone. The property of the dead-zone is discretized. Mean value theorem is used to transform the systems into a special form. The unknown functions in the input–output model are approximated using the radial basis function neural networks. Compared with the results for the discrete non-symmetric dead-zone, this article presents a new algorithm to reduce the computational burden. Lyapunov analysis method is utilized to prove that all the signals in the closed-loop systems are semi-global uniformly ultimately bounded. The tracking error is proved to converge to a small set around the zero. A simulation example provided to illustrate the effectiveness of the control schemes.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-012-1080-5