Abstract and Applied Analysis

Neural Network Inverse Model Control Strategy: Discrete-Time Stability Analysis for Relative Order Two Systems

M. A. Hussain, Jarinah Mohd Ali, and M. J. H. Khan

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Abstract

This paper discusses the discrete-time stability analysis of a neural network inverse model control strategy for a relative order two nonlinear system. The analysis is done by representing the closed loop system in state space format and then analyzing the time derivative of the state trajectory using Lyapunov’s direct method. The analysis shows that the tracking output error of the states is confined to a ball in the neighborhood of the equilibrium point where the size of the ball is partly dependent on the accuracy of the neural network model acting as the controller. Simulation studies on the two-tank-in-series system were done to complement the stability analysis and to demonstrate some salient results of the study.

Article information

Source
Abstr. Appl. Anal., Volume 2014 (2014), Article ID 645982, 11 pages.

Dates
First available in Project Euclid: 2 October 2014

Permanent link to this document
https://projecteuclid.org/euclid.aaa/1412276988

Digital Object Identifier
doi:10.1155/2014/645982

Mathematical Reviews number (MathSciNet)
MR3212440

Zentralblatt MATH identifier
07022817

Citation

Hussain, M. A.; Mohd Ali, Jarinah; Khan, M. J. H. Neural Network Inverse Model Control Strategy: Discrete-Time Stability Analysis for Relative Order Two Systems. Abstr. Appl. Anal. 2014 (2014), Article ID 645982, 11 pages. doi:10.1155/2014/645982. https://projecteuclid.org/euclid.aaa/1412276988


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