Paper Info

Title | ||
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Adaptive fuzzy backstepping output feedback control for a class of uncertain stochastic nonlinear system in pure-feedback form |

Abstract | ||
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This paper is concerned with the problem of adaptive fuzzy output feedback for a class of uncertain stochastic pure-feedback nonlinear systems with immeasurable states. With the help of fuzzy logic systems to approximate the unknown nonlinear functions, and a fuzzy state observer is designed to estimate the unmeasured states. By incorporating the filtered signals into the backstepping recursive design, a fuzzy adaptive output feedback control scheme is developed. It is proven that all the signals of the closed-loop system are bounded in probability, and also that the observer errors and the output of the system converge to a small neighborhood of the origin by appropriate choice of the design parameters. Simulation studies are included to illustrate the effectiveness of the proposed approach. |

Year | DOI | Venue |
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2013 | 10.1016/j.neucom.2013.06.036 | Neurocomputing |

Keywords | Field | DocType |

uncertain stochastic pure-feedback nonlinear,feedback control,design parameter,backstepping recursive design,fuzzy state observer,system converge,pure-feedback form,adaptive fuzzy backstepping output,adaptive fuzzy output feedback,fuzzy adaptive output feedback,fuzzy logic system,observer error,uncertain stochastic nonlinear system,closed-loop system,state observer | State observer,Mathematical optimization,Backstepping,Nonlinear system,Control theory,Nonlinear control,Fuzzy logic,Adaptive neuro fuzzy inference system,Observer (quantum physics),Mathematics,Bounded function | Journal |

Volume | ISSN | Citations |

122, | 0925-2312 | 14 |

PageRank | References | Authors |

0.56 | 36 | 3 |

Authors (3 rows)

Cited by (14 rows)

References (36 rows)

Name | Order | Citations | PageRank |
---|---|---|---|

Yang Gao | 1 | 14 | 0.56 |

Shaocheng Tong | 2 | 8625 | 289.74 |

Yongming Li | 3 | 4931 | 147.76 |