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Adaptive event-triggered prescribed performance learning synchronization for complex dynamical networks with unknown time-varying coupling strength

机译:具有未知时变耦合强度的复杂动态网络的自适应事件触发规定的性能学习同步

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摘要

In this paper, we focus on investigating the prescribed performance synchronization problems of complex dynamical networks with unknown time-varying coupling strength by learning control method. An event-triggered control protocol is designed, and a sufficient condition of synchronization is also given based on Lyapunov stability theory, which can ensure that the sates of all nodes synchronize to the specified target trajectory, and the synchronization errors meet the prescribed performance requirements. The main advantage of the protocol is not only to ensure the transient performance and convergence of synchronization errors of complex dynamic networks with unknown time-varying coupling strength, but also to avoid the continuous communication among network nodes under the event-triggered communication mechanism which can reduce the number of information updates. In addition, the Zeno behavior is avoided in communication process of the networks. At last, the effectiveness of the proposed theoretic results obtained is verified via the applications of the complex dynamical networks with Chua's circuit and a simple pendulum dynamics.
机译:本文通过学习控制方法研究了通过学习控制方法研究了具有未知时变耦合强度的复杂动态网络规定的性能同步问题。设计了事件触发的控制协议,并且还基于Lyapunov稳定性理论给出了足够的同步条件,这可以确保所有节点的SATE同步到指定的目标轨迹,并且同步误差符合规定的性能要求。该协议的主要优点不仅是为了确保具有未知时变耦合强度的复杂动态网络同步误差的瞬态性能和收敛性,而且还避免了在可以的事件触发的通信机制下的网络节点之间的连续通信减少信息更新的数量。此外,在网络的通信过程中避免了ZENO行为。最后,通过与Chua电路的复杂动态网络的应用和简单的摆动动力学来验证所获得的提出的理论结果的有效性。

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