Iterative Learning Control Design of Switched Systems With Markovian Jump Parameters via Fuzzy Approach

In this paper, based on Takagi-Sugeno (T-S) approach the work is concerned with the iterative learning control (ILC) problem for a class of switched systems with data packet dropouts. The designed scheme is described by a class of Markovian switching systems with transition probabilities which are t...

Full description

Bibliographic Details
Main Authors: Yang Wang, Xiaolei Ji
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8808900/
id doaj-2776a9ac9da24ce9811e4c987f641a18
record_format Article
spelling doaj-2776a9ac9da24ce9811e4c987f641a182021-03-30T00:00:43ZengIEEEIEEE Access2169-35362019-01-01711816211817210.1109/ACCESS.2019.29366538808900Iterative Learning Control Design of Switched Systems With Markovian Jump Parameters via Fuzzy ApproachYang Wang0https://orcid.org/0000-0002-7281-1721Xiaolei Ji1Department of Mathematics and Physics, Shenyang University of Chemical Technology, Shenyang, ChinaDepartment of Mathematics and Physics, Shenyang University of Chemical Technology, Shenyang, ChinaIn this paper, based on Takagi-Sugeno (T-S) approach the work is concerned with the iterative learning control (ILC) problem for a class of switched systems with data packet dropouts. The designed scheme is described by a class of Markovian switching systems with transition probabilities which are time-variant in a network environment. The links of network communications between controllerto-actuator (C/A) and sensor-to-controller (S/C) are unreliable. In terms of the construction of twodimensional (2D) T-S model, a novel composite strategy of 2D fuzzy iterative learning output feedback control is proposed. The sufficient conditions on stochastic stability are obtained by the 2D Lyapunov stability theory. Furthermore, the dynamics of the closed-loop are guaranteed to be stochastically stable and the desired H<sub>&#x221E;</sub> performance is also provided. The solutions of the ILC controller are derived by the application of the cone complementarity linearisation (CCL) procedure. Finally, a numerical simulation is illustrated to show the validity of the design.https://ieeexplore.ieee.org/document/8808900/Iterative learning controlMarkovian jump systemsTakagi-Sugeno fuzzydata packet dropouttime variant
collection DOAJ
language English
format Article
sources DOAJ
author Yang Wang
Xiaolei Ji
spellingShingle Yang Wang
Xiaolei Ji
Iterative Learning Control Design of Switched Systems With Markovian Jump Parameters via Fuzzy Approach
IEEE Access
Iterative learning control
Markovian jump systems
Takagi-Sugeno fuzzy
data packet dropout
time variant
author_facet Yang Wang
Xiaolei Ji
author_sort Yang Wang
title Iterative Learning Control Design of Switched Systems With Markovian Jump Parameters via Fuzzy Approach
title_short Iterative Learning Control Design of Switched Systems With Markovian Jump Parameters via Fuzzy Approach
title_full Iterative Learning Control Design of Switched Systems With Markovian Jump Parameters via Fuzzy Approach
title_fullStr Iterative Learning Control Design of Switched Systems With Markovian Jump Parameters via Fuzzy Approach
title_full_unstemmed Iterative Learning Control Design of Switched Systems With Markovian Jump Parameters via Fuzzy Approach
title_sort iterative learning control design of switched systems with markovian jump parameters via fuzzy approach
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description In this paper, based on Takagi-Sugeno (T-S) approach the work is concerned with the iterative learning control (ILC) problem for a class of switched systems with data packet dropouts. The designed scheme is described by a class of Markovian switching systems with transition probabilities which are time-variant in a network environment. The links of network communications between controllerto-actuator (C/A) and sensor-to-controller (S/C) are unreliable. In terms of the construction of twodimensional (2D) T-S model, a novel composite strategy of 2D fuzzy iterative learning output feedback control is proposed. The sufficient conditions on stochastic stability are obtained by the 2D Lyapunov stability theory. Furthermore, the dynamics of the closed-loop are guaranteed to be stochastically stable and the desired H<sub>&#x221E;</sub> performance is also provided. The solutions of the ILC controller are derived by the application of the cone complementarity linearisation (CCL) procedure. Finally, a numerical simulation is illustrated to show the validity of the design.
topic Iterative learning control
Markovian jump systems
Takagi-Sugeno fuzzy
data packet dropout
time variant
url https://ieeexplore.ieee.org/document/8808900/
work_keys_str_mv AT yangwang iterativelearningcontroldesignofswitchedsystemswithmarkovianjumpparametersviafuzzyapproach
AT xiaoleiji iterativelearningcontroldesignofswitchedsystemswithmarkovianjumpparametersviafuzzyapproach
_version_ 1724188746006396928