Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systems

Shaocheng Tong; Changliang Liu; Yongming Li

International Journal of Applied Mathematics and Computer Science (2010)

  • Volume: 20, Issue: 4, page 637-653
  • ISSN: 1641-876X

Abstract

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In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy logic systems are used to approximate unstructured uncertainties, and K-filters are designed to estimate unmeasured states. By combining backstepping design and a small-gain theorem, a stable adaptive fuzzy output feedback control scheme is developed. It is proven that the proposed adaptive fuzzy control approach can guarantee the all the signals in the closed-loop system are uniformly ultimately bounded, and the output of the controlled system converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by a simulation example and some comparisons.

How to cite

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Shaocheng Tong, Changliang Liu, and Yongming Li. "Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systems." International Journal of Applied Mathematics and Computer Science 20.4 (2010): 637-653. <http://eudml.org/doc/208013>.

@article{ShaochengTong2010,
abstract = {In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy logic systems are used to approximate unstructured uncertainties, and K-filters are designed to estimate unmeasured states. By combining backstepping design and a small-gain theorem, a stable adaptive fuzzy output feedback control scheme is developed. It is proven that the proposed adaptive fuzzy control approach can guarantee the all the signals in the closed-loop system are uniformly ultimately bounded, and the output of the controlled system converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by a simulation example and some comparisons.},
author = {Shaocheng Tong, Changliang Liu, Yongming Li},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {nonlinear systems; adaptive fuzzy control; backstepping; small-gain approach; K-filters; -filters},
language = {eng},
number = {4},
pages = {637-653},
title = {Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systems},
url = {http://eudml.org/doc/208013},
volume = {20},
year = {2010},
}

TY - JOUR
AU - Shaocheng Tong
AU - Changliang Liu
AU - Yongming Li
TI - Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systems
JO - International Journal of Applied Mathematics and Computer Science
PY - 2010
VL - 20
IS - 4
SP - 637
EP - 653
AB - In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy logic systems are used to approximate unstructured uncertainties, and K-filters are designed to estimate unmeasured states. By combining backstepping design and a small-gain theorem, a stable adaptive fuzzy output feedback control scheme is developed. It is proven that the proposed adaptive fuzzy control approach can guarantee the all the signals in the closed-loop system are uniformly ultimately bounded, and the output of the controlled system converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by a simulation example and some comparisons.
LA - eng
KW - nonlinear systems; adaptive fuzzy control; backstepping; small-gain approach; K-filters; -filters
UR - http://eudml.org/doc/208013
ER -

References

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