Integral-Based Memory Event-Triggered Controller Design for Uncertain Neural Networks with Control Input Missing

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In this paper, the controller design problem for uncertain neural networks (NNs) with control input missing is addressed under an event-triggered (ET) scheme. First, under the zero-input method, the closed-loop system is modeled as a switched system which includes a stable subsystem and an unstable subsystem. Next, a novel integral-based memory event-triggered (IMET) scheme is designed, which can prevent Zeno behavior. The proposed IMET scheme is designed over a specified memory interval; thus, it can make full use of the historical state information, thereby reducing the adverse impact caused by packet dropouts. Then, with the analysis method of switched systems, a piecewise time-dependent Lyapunov functional is designed, and low conservative conditions are derived to ensure the exponential stability of the switched closed-loop system. Meanwhile, the constraints on the packet loss rate and the average dwell time are established. Moreover, the design of the controller gain is also given. Finally, the feasibility of IMET is verified using an example.

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