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Relative Degrees and Implicit Function-Based Control of Discrete-Time Noncanonical Form Neural Network Systems | IEEE Journals & Magazine | IEEE Xplore

Relative Degrees and Implicit Function-Based Control of Discrete-Time Noncanonical Form Neural Network Systems


Abstract:

This paper studies the relative degrees of discrete-time neural network systems in a general noncanonical form, and develops a new feedback control scheme for such system...Show More

Abstract:

This paper studies the relative degrees of discrete-time neural network systems in a general noncanonical form, and develops a new feedback control scheme for such systems, based on implicit function theory and feedback linearization. After time-advance operation on output of such systems, the output dynamics nonlinearly depends on the control input. To address this issue, we use implicit function theory to define the relative degrees, and to establish a normal form. Then, an implicit function equation solution-based control scheme and an iterative solution-based control scheme are proposed, which ensure not only the closed-loop stability but also the output tracking for the controlled plant. An adaptive control framework for the controlled plant with uncertainties is also presented to illustrate the basic design procedure. The simulation results are given to demonstrate the desired system performance.
Published in: IEEE Transactions on Cybernetics ( Volume: 50, Issue: 2, February 2020)
Page(s): 514 - 524
Date of Publication: 26 September 2018

ISSN Information:

PubMed ID: 30273176

Funding Agency:


References

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