The modeling of memcapacitor oscillator motion with ANN and its nonlinear control application

Abstract

In this study, a memcapacitor-based chaotic oscillator and its engineering applications are discussed. Also nonlinear feedback control method is applied to drive the system to equilibrium and the modeling of the memcapacitor system with Artificial Neural Networks (ANN) as engineering applications. Some dynamical properties such as phase portraits, equilibrium points and bifurcation of the proposed system are investigated. A video of the chaotic memcapacitor circuit was created using phase portraits. The image processing technique was used to determine the object in the video. ANN is trained by both a backpropagation method and the Levenberg-Marquardt method. It is shown that the states of the chaotic memcapacitor oscillator system trained with ANN can be reconstructed and modeled in this way and the results are given. © 2021 Elsevier Inc. All rights reserved.