Mean-Square Admissibility Analysis and Controller Design for It ô -Type Stochastic Singular Systems

The issues of mean-square admissibility and synthesis of It<inline-formula> <tex-math notation="LaTeX">$\hat {o}$ </tex-math></inline-formula>-type stochastic singular systems (SSSs) under Brownian parameter perturbations are introduced in this article. For ease of computation, a novel sufficient condition is given to guarantee autonomous systems are mean-square admissible via strict linear matrix inequalities(LMIs). Furthermore, own to the measurable of the system states, both state feedback controller and observer-based controller (OBC) for It<inline-formula> <tex-math notation="LaTeX">$\hat {o}$ </tex-math></inline-formula>-type SSSs are investigated. However, in It<inline-formula> <tex-math notation="LaTeX">$\hat {o}$ </tex-math></inline-formula>-type SSSs, because the state of the system and the observer can be affected by Brownian fluctuation, it is not feasible that the observer and control gains design are completely separate. To this end, an innovative design approach is also proposed to solve the controller and observer parameters simultaneously in form of strict LMIs. Finally, three examples are introduced to demonstrate the effectiveness of the proposed method.

Abstract licence: CC BY-NC-ND

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.