Terminal Sliding Mode Control Using Adaptive Fuzzy-Neural Observer

We propose a terminal sliding mode control (SMC) law based on adaptive fuzzy-neural observer for nonaffine nonlinear uncertain system. First, a novel nonaffine nonlinear approximation algorithm is proposed for observer and controller design. Then, an adaptive fuzzy-neural observer is introduced to i...

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Main Authors: Dezhi Xu, Bin Jiang, Moshu Qian, Jing Zhao
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2013/958958
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spelling doaj-1fb729a8b7e04977a4649f4d255706902020-11-24T22:13:52ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/958958958958Terminal Sliding Mode Control Using Adaptive Fuzzy-Neural ObserverDezhi Xu0Bin Jiang1Moshu Qian2Jing Zhao3College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaWe propose a terminal sliding mode control (SMC) law based on adaptive fuzzy-neural observer for nonaffine nonlinear uncertain system. First, a novel nonaffine nonlinear approximation algorithm is proposed for observer and controller design. Then, an adaptive fuzzy-neural observer is introduced to identify the simplified model and resolve the problem of the unavailability of the state variables. Moreover, based on the information of the adaptive observer, the terminal SMC law is designed. The Lyapunov synthesis approach is used to guarantee a global uniform ultimate boundedness property of the state estimation error and the asymptotic output tracking of the closed-loop control systems in spite of unknown uncertainties/disturbances, as well as all the other signals in the closed-loop system. Finally, using the designed terminal sliding mode controller, the simulation results on the dynamic model demonstrate the effectiveness of the proposed new control techniques.http://dx.doi.org/10.1155/2013/958958
collection DOAJ
language English
format Article
sources DOAJ
author Dezhi Xu
Bin Jiang
Moshu Qian
Jing Zhao
spellingShingle Dezhi Xu
Bin Jiang
Moshu Qian
Jing Zhao
Terminal Sliding Mode Control Using Adaptive Fuzzy-Neural Observer
Mathematical Problems in Engineering
author_facet Dezhi Xu
Bin Jiang
Moshu Qian
Jing Zhao
author_sort Dezhi Xu
title Terminal Sliding Mode Control Using Adaptive Fuzzy-Neural Observer
title_short Terminal Sliding Mode Control Using Adaptive Fuzzy-Neural Observer
title_full Terminal Sliding Mode Control Using Adaptive Fuzzy-Neural Observer
title_fullStr Terminal Sliding Mode Control Using Adaptive Fuzzy-Neural Observer
title_full_unstemmed Terminal Sliding Mode Control Using Adaptive Fuzzy-Neural Observer
title_sort terminal sliding mode control using adaptive fuzzy-neural observer
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2013-01-01
description We propose a terminal sliding mode control (SMC) law based on adaptive fuzzy-neural observer for nonaffine nonlinear uncertain system. First, a novel nonaffine nonlinear approximation algorithm is proposed for observer and controller design. Then, an adaptive fuzzy-neural observer is introduced to identify the simplified model and resolve the problem of the unavailability of the state variables. Moreover, based on the information of the adaptive observer, the terminal SMC law is designed. The Lyapunov synthesis approach is used to guarantee a global uniform ultimate boundedness property of the state estimation error and the asymptotic output tracking of the closed-loop control systems in spite of unknown uncertainties/disturbances, as well as all the other signals in the closed-loop system. Finally, using the designed terminal sliding mode controller, the simulation results on the dynamic model demonstrate the effectiveness of the proposed new control techniques.
url http://dx.doi.org/10.1155/2013/958958
work_keys_str_mv AT dezhixu terminalslidingmodecontrolusingadaptivefuzzyneuralobserver
AT binjiang terminalslidingmodecontrolusingadaptivefuzzyneuralobserver
AT moshuqian terminalslidingmodecontrolusingadaptivefuzzyneuralobserver
AT jingzhao terminalslidingmodecontrolusingadaptivefuzzyneuralobserver
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