Tighter Interval Estimation for Discrete-Time Linear Systems With a New Dynamic Triggering Approach
Mouquan Shen, Yang Gu, Qing‐Guo Wang, Zheng‐Guang Wu, Ju H. Park
Abstract
This paper is concerned with interval estimation for discrete-time linear systems with unknown disturbances. An improved proportional integral configuration is built for an iterative interval observer to get tighter estimation intervals for system states and disturbances. A novel dynamic triggering scheme is put forward to reduce unnecessary transmissions between sensor output to the observer. In this scheme, the threshold could be dynamically adjusted with system running stages. Moreover, this scheme covers some existing results as special cases. A structured separation method is employed to solve the control gain and the observer gains in terms of linear matrix inequalities. A comparison simulation study is provided to show the validity of the supplied estimation configuration and the triggering scheme.