In collaboration with Payame Noor University and Iranian Society of Instrumentation and Control Engineers

Document Type : Research Article

Authors

1 School of Economics and Statistics‎, ‎Guangzhou University‎, ‎P.O‎. ‎Box‎. ‎510006‎, ‎Guangzhou‎, ‎China‎

2 Electrical and Computer Engineering Department‎, ‎University of Windsor‎, ‎Windsor‎, ‎ON‎, ‎Canada

3 Department of Automation‎, Biomechanics and Mechatronics‎, ‎Lods University of Technology‎, ‎Poland

Abstract

The present study introduces a kind of fractional-order Hopfield neural network (FOHNN)‎, ‎and its complex dynamic behavior is investigated through chaos analyses‎. ‎With the use of phase space analysis and bifurcation diagrams and maximal Lyapunov exponent (MLE) it is demonstrated that for the values of 0.87 < α < 1‎, as the fractional-order (FO)‎, ‎the dynamical behavior of the mentioned FOHNN is chaotic‎. ‎Then‎, ‎the bounded trait of chaotic systems is utilized to derive an adaptive model-free control technique to suppress of complex dynamics of the FOHNN‎. ‎Furthermore‎, ‎according to the matrix analysis theorem of non-integer-order systems and the adaptive model-free control methodology‎, ‎analytical consequences of the designed controller are evidenced‎. ‎Eventually‎, ‎two examples are reported to illustrate the applicability of the mentioned model-free control method.

Keywords

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