Discontinuous Event-Triggered Control for Local Stabilization of Memristive Neural Networks With Actuator Saturation: Discrete- and Continuous-Time Lyapunov Methods
| Autor: | Hao Shen, Jianwei Xia, Zhen Wang, Yingjie Fan, Xia Huang |
|---|---|
| Rok vydání: | 2023 |
| Předmět: |
Lyapunov function
Artificial neural network Basis (linear algebra) Computer Networks and Communications Computer science Interval (mathematics) Positive-definite matrix Upper and lower bounds Computer Science Applications symbols.namesake Artificial Intelligence Control theory symbols Piecewise Convex combination Software |
| Zdroj: | IEEE Transactions on Neural Networks and Learning Systems. 34:1988-2000 |
| ISSN: | 2162-2388 2162-237X |
| Popis: | In this article, the local stabilization problem is investigated for a class of memristive neural networks (MNNs) with communication bandwidth constraints and actuator saturation. To overcome these challenges, a discontinuous event-trigger (DET) scheme, consisting of the rest interval and work interval, is proposed to cut down the triggering times and save the limited communication resources. Then, a novel relaxed piecewise functional is constructed for closed-loop MNNs. The main advantage of the designed functional consists in that it is positive definite only in the work intervals and the sampling instants but not necessarily inside the rest intervals. With the aid of extended reciprocally convex combination lemma, generalized sector condition, and some inequality techniques, two local stabilization criteria are established on the basis of both the discrete- and continuous-time Lyapunov methods. The proposed analysis technique fully takes advantage of the looped-functional and the event-trigger mechanism. Moreover, two optimization schemes are, respectively, established to design the control gain and enlarge the estimates of the admissible initial conditions (AICs) and the upper bound of rest intervals. Finally, some comparison results are given to validate the superiority of the proposed method. |
| Databáze: | OpenAIRE |
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