Experimental verification of quasi-periodic-orbit stabilization using a switched-capacitor chaotic neural network circuit

Abstract

Pole assignment control for stabilizing a quasi-periodic orbit in a discrete-time dynamical system has been previously proposed. In this paper, the pole assignment method is applied to a switched-capacitor chaotic neural network circuit. For circuit experiments in which there are unknown circuit characteristics and parameters, and inevitable noise, the control method is modified by introducing new control input signals. As a result, the quasi-periodic orbits are successfully stabilized through pole assignment control. In order to confirm the quasi-periodicity of the obtained orbits, bifurcation diagrams and phase-plane portraits are provided. In addition, a statistical test designed for noisy experimental data, in particular, further confirms the quasi-periodicity. Through circuit experiments, the feasibility, usefulness, efficacy, and robustness of pole assignment control for quasi-periodic orbits are verified.