基于新息约束的大规模系统的自适应事件触发故障估计

Adaptive-Event-Triggered Fault Estimation for Large-Scale Systems via Innovation Constraints

摘要: 本文研究了具有测量输出量化的大规模系统的故障估计问题，其中子估计器之间的通信拓扑与子系统的物理耦合结构相同。针对信道带宽有限的问题，提出了一种新的自适应事件触发方案来控制子估计器之间的数据传输。利用李雅普诺夫分析方法，得到了保证估计误差的动力学在均方意义下指数最终有界的充分条件。利用矩阵不等式技术，得到了期望滤波器增益的解析表达式和滤波误差的最终界。最后，通过一个数值例子验证了该设计方法的有效性。

Abstract: This paper focuses on the fault estimation issues of large-scale systems with measurements output, where the communication topology among sub-estimators is the same with the physical coupling structure of subsystems. Considering the limited channel bandwidth, a novel adaptive event-triggered scheme is proposed for governing the data transmission among sub-estimators. With the help of Lyapunov analysis approaches, sufficient conditions are derived to ensure that the dynamics of estimation errors is exponentially ultimately bounded in mean-square sense. Furthermore, an analytic formula of the desired filter gain and the ultimate bound of filtering errors are obtained through the utilization of matrix inequality techniques. Finally, one numerical example is given to testify the effectiveness of the proposed design approach.