Event-Triggered and Asynchronous Reduced-Order Filtering Codesign for Fuzzy Markov Jump Systems
研究了Takagi-Sugeno模糊马尔可夫跳变系统在事件触发机制下的降阶耗散滤波问题，通过隐马尔可夫模型处理滤波器与被估计系统间的异步性，并利用线性矩阵不等式设计滤波器以保证系统随机稳定和严格耗散。
This article is devoted to the investigation of reduced-order dissipative filtering for Takagi–Sugeno (T–S) fuzzy Markov jump systems with the event-triggered mechanism. For the proposed event-triggered mechanism, its threshold parameter is constructed as a special diagonal matrix which can improve system performance by flexibly adjusting the matrix elements. Due to the impact of the sampling behaviors and the environmental disturbance, the asynchronization between the filter and the estimated system is considered in this article, which can be characterized by the hidden Markov model. Through handling the linear matrix inequalities (LMIs) with some slack matrices, event-triggered fuzzy filters are designed to guarantee the resulting system is stochastically stable and strictly dissipative. The proposed filter parameters are obtained by solving LMIs. Ultimately, both the effectiveness and advantages of the proposed reduced-order filter with the event-triggered mechanism are verified by a practical example.