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首页> 外文期刊>IEEE transactions on industrial informatics >Dynamic Event-Triggered State Estimation for Continuous-Time Polynomial Nonlinear Systems With External Disturbances
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Dynamic Event-Triggered State Estimation for Continuous-Time Polynomial Nonlinear Systems With External Disturbances

机译：用于外部干扰的连续时间多项式非线性系统的动态事件触发状态估计

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摘要

This article is concerned with the problem of state estimation for continuous-time polynomial nonlinear (CTPN) systems with unknown but bounded disturbances. The Taylor polynomial expansion technique is employed to realize the conversion from polynomial nonlinear systems to linear-parameter-varying systems related to the estimate. Moreover, for the purpose of saving the communication resources, an event-triggered sampling scheme is first introduced in the state estimation for CTPN systems, where the event-triggered condition is changed dynamically and the Zeno behavior is excluded. Based on the matrix inequality approach, a sufficient condition is derived in terms of the parameter-dependent linear matrix inequality (LMI) such that the estimation error system is input-to-state stable. Then, the desired estimator parameters can be obtained by solving the parameter-dependent LMI via the sum of squares decomposition technique. Finally, two examples with one concerning the permanent magnet synchronous motor systems are provided to demonstrate the usefulness of proposed method.
机译：本文涉及具有未知但有界扰动的连续时间多项式非线性（CTPN）系统的状态估计问题。采用泰勒多项式膨胀技术，实现从多项式非线性系统转换为与估计有关的线性参数变化系统。此外，为了保存通信资源，首先在CTPN系统的状态估计中引入事件触发的采样方案，其中发生事件触发的条件动态地改变，并且排除ZENO行为。基于矩阵不等式方法，就参数相关的线性矩阵不等式（LMI）来导出足够的条件，使得估计误差系统被输入到状态稳定。然后，可以通过通过平方分解技术的总和来求解参数相关的LMI来获得所需的估计器参数。最后，提供了一个关于永磁同步电动机系统的两个示例，以证明所提出的方法的有用性。

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