A Double Integral Noise-Tolerant Fuzzy ZNN Model for TVSME Applied to the Synchronization of Chua's Circuit Chaotic System

Taking advantage of the burgeoning zeroing neural network (ZNN) and the widely used fuzzy logic system (FLS), a novel double integral noise-tolerant fuzzy ZNN (DINTFZNN) model for solving the time-varying Sylvester matrix equation (TVSME) is proposed in this article. The special feature of the DINTFZNN model lies in the adoption of a double integral design formula, which makes the DINTFZNN model has superb robustness, that is, it can effectively suppress not only linear noise but also quadratic noise. In addition, the DINTFZNN model utilizes a fuzzy parameter generated by FLS as the design parameter, which can adaptively adjust the convergence rate and enhance the robustness and adaptability of the DINTFZNN model. Theories have rigorously demonstrated the convergence and robustness of the DINTFZNN model. By the comparison experiments with the single integral noise-tolerant ZNN model, the superiority of the DINTFZNN model is further confirmed. In the end, the design method of the DINTFZNN model is applied to the synchronization of Chua's circuit chaotic systems, which epitomizes its excellent applicability.