Open AccessFuzzy dynamic output‐feedback control of non‐linear networked discrete‐time system with missing measurements
Author(s) -
Li Hongyi,
Wu Chengwei,
Feng Zhiguang
Publication year - 2015
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.2014.0410
Subject(s) - control theory (sociology) , fuzzy logic , bernoulli distribution , fuzzy control system , lyapunov function , controller (irrigation) , computer science , bernoulli's principle , convex optimization , mathematics , regular polygon , nonlinear system , control (management) , random variable , engineering , artificial intelligence , statistics , physics , geometry , quantum mechanics , aerospace engineering , agronomy , biology
This article studies the problem of H ∞ dynamic output‐feedback control of non‐linear networked discrete‐time systems with data packet dropouts. Specifically, the data missing happens randomly from the sensor to the controller and the controller to the actuator. A sequence of independent variables obeying the Bernoulli random binary distribution is introduced to account for the measurement missing. The Takagi–Sugeno fuzzy model is used to describe the non‐linear plant. In addition, the strategy of parallel distributed compensation is adopted to design the fuzzy dynamic output‐feedback controller. Here, attention is focused on obtaining the sufficient conditions to guarantee the closed‐loop system to be stochastically stable as well as the prescribed H ∞ performance. An approach based on fuzzy Lyapunov function is developed to solve it. To tackle the non‐convex problem, the cone‐complementarity linearisation procedure is adopted. Finally, a numerical example is employed to show the usefulness of the proposed result.