Open AccessFinite‐time control for discrete time‐varying systems with randomly occurring non‐linearity and missing measurements
Author(s) -
Shi Yujing,
Tang Yu,
Li Shanqiang
Publication year - 2017
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2016.1367
Subject(s) - control theory (sociology) , discrete time and continuous time , bernoulli's principle , mathematics , linearity , controller (irrigation) , stability (learning theory) , missing data , conditional probability , bernoulli distribution , linear matrix inequality , computer science , control (management) , mathematical optimization , random variable , statistics , engineering , agronomy , electrical engineering , artificial intelligence , machine learning , biology , aerospace engineering
In this study, the finite‐time control problem is studied for discrete time‐varying systems with randomly occurring non‐linearity and missing measurements. The randomly occurring non‐linearity is modelled according to a Bernoulli distributed white sequence with a known conditional probability. The missing measurements phenomenon is assumed to occur in a random way and the missing probabilities are time‐varying with known upper and lower bounds. Two sufficient conditions are established for the existence of the state feedback and output feedback controllers, which guarantee the finite‐time stochastic stability of the closed‐loop systems. The recursive linear matrix inequality approach is employed to design the desired controller gains. A numerical example is provided to illustrate the effectiveness of the obtained results.