ABSTRACT
This chapter addresses the event-triggered H∞ state estimation problem for state-saturated systems. In this system under consideration, a saturation function is introduced to constrain the state variables to stay within a bounded set. Firstly, the event-triggered distributed H∞ state estimation problem is investigated for a class of state-saturated systems with randomly occurring mixed delays over sensor networks. The mixed delays, which comprise both discrete and distributed delays, are allowed to occur in a random manner governed by two mutually independent Bernoulli distributed random variables. Moreover, the event-triggered H∞ state estimation problem is also studied for a class of state-saturated complex networks subject to quantization effects as well as randomly occurring distributed delays. The main purpose is to design event-triggered state estimators such that the error dynamics of state estimation is exponentially mean-square stable with a prescribed H∞ performance index. Sufficient conditions are derived via intensive stochastic analysis to guarantee the existence of the desired estimators, and the parameters of the desired estimators are then obtained in light of the feasibility of certain sets of matrix inequalities. Finally, some numerical examples are employed to illustrate the usefulness of the proposed event-triggered estimation algorithms.
