Fuzzy Sampled-Data Stabilization of Hidden Oscillations in a Memristor-Based Dynamical System

In the manuscript, we report the dynamics of the Takagi-Sugeno (T-S) fuzzy memristor-based hidden system via sampled-data control. For an open-loop formulation, the system dynamics are studied. We found extreme events, hidden attractors, and trivial period doubling scenarios and confirmed them through numerical, analytical, statistical and experimental analyses. Furthermore, to enable stability analysis and control combination, the (T-S) fuzzy algorithm is employed to control the dynamics of a nonlinear system. First, we designed the sampled data fuzzy controller (SDFC) for the proposed system. Second, the Lyapunov-Krasovskii functional (LKF) strategy, novel integral inequality mechanisms, and certain sufficient conditions are determined by deriving the linear matrix inequalities (LMIs), which ensure the asymptotic stability of the system. Moreover, the sampled data control gains are computed for the large sampling interval, and numerically obtained results confirm the theoretical results. Additionally, a simple real-time analog electronic circuit is constructed, and experimental data is obtained, and finally, numerically simulated results were verified through MATLAB.