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...
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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>∞</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>∞</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 |