Protocol-Based Asynchronous Filtering for Interval Type-2 Fuzzy Systems With Time-Varying Saturation Function
Abstract
This study is concerned with protocol-based asynchronous filtering for interval type-2 (IT2) fuzzy systems subject to time-varying saturation functions. Two mutually independent Markov processes are proposed to characterize the random manners of intermittently failure and transmission sequence of sensor nodes, and a new joint Markov process is formulated by adopting the merging technique. Aiming at curbing the data collision and improving network utilization in the restricted network, an ETRP is implemented to govern whether to orchestrate the packets and which one to be launched simultaneously. A novel asynchronous filter is formulated under the constraint of saturation with the hope to improve filtering performance. This construction involves the dynamic adaptation of the saturation level in tandem with the estimation error. Additionally, the mismatched modes between the newly joined Markov process and filter are characterized by a hidden Markov model. Eventually, two examples are applied to verify the availability of the theoretical results.