Finite time dynamic analysis of memristor-based fuzzy NNs with inertial term: Nonreduced-order approach

The finite-time synchronization (FTS) for memristor-based fuzzy neural networks with inertial term (MFINNs) is studied in this literature. In order to enhance the performance, efficiency and adaptability of the system to complex application scenarios, the memristor and inertial term are considered in the fuzzy neural network (FNNs). Different from the corresponding researches on exponential/asymptotic synchronization, the FTS of MFINNs is first investigated. This work directly analyze the second-order system via nonreduced-order approach, which can better reflect the second-order system because they do not lose any important kinetic information.Subsequently, fuzzy state-feedback and adaptive control schemes are constructed to guarantee the FTS of MFINNs. The algebraic conditions on the FTS of MFINNs are obtained by selecting a suitable Lyapunov–Krasovskii functional. At last, a numerical simulation is presented to substantiate the advantages of the proposed results. And some comparisons with the latest method are demonstrated.