Extended dissipative asynchronous filtering for T–S fuzzy switched systems with partial transition descriptions and incomplete measurements. (August 2020) - Shan, Yaonan; Liu, Xinzhi; She, Kun; Zhong, Shouming; Cheng, Jun; Zhang, Xiaojun
Abstract: This paper analyzes the problem of extended dissipative asynchronous filtering for Markov jump T–S fuzzy systems (MJTSFSs) with sensor failures and incomplete measurements. The highlight of this work lies in the fact that we introduce an asynchronous filter (AF) in which mode transition probability matrix (TPM) is non-homogeneous. "Asynchronous" means that the switching of the filters to be designed may be different from that of the systems. Thanks to this AF, partial information of system modes can be fully utilized to achieve the improved and extended dissipative performance including the dissipativity, passivity, H ∞ performance and l 2 − l ∞ performance. Specifically, we first attempt to show that the transition probability information (TPI) of the two different Markov chains is not fully known, which can be regarded as an extension of existing work. In the meantime, this is also an arduous problem to be solved in this article. Additionally, with respect to the asynchronous filtering of MJTSFSs, we not only consider that sensor failures occur randomly in the filter systems, but also that research that the measured output is assumed to be quantized by the logarithmic quantizer. Then, an AF is designed for MJTSFSs with sensor failures and incomplete transition probability (ITP) for the first time. Finally, through three examples, the effects of sensor failures, quantizers, and degrees of asynchronism on system performance are examined.