<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

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

Department of Mathematics, Liaoning University of Technology, Jinzhou, 121001, People's Republic of China

International Journal of Applied Mathematics and Computer Science

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...

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

Online veröffentlicht: 20. Dez. 2010

Seitenbereich: 637 - 653

DOI: https://doi.org/10.2478/v10006-010-0047-x

Schlüsselwörter
nonlinear systems, adaptive fuzzy control, backstepping, small-gain approach, K-filters

This content is open access.

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

Online veröffentlicht: 20. Dez. 2010

Seitenbereich: 637 - 653

DOI: https://doi.org/10.2478/v10006-010-0047-x

Schlüsselwörternonlinear systems, adaptive fuzzy control, backstepping, small-gain approach, K-filters

This content is open access.

Schlüsselwörter
nonlinear systems, adaptive fuzzy control, backstepping, small-gain approach, K-filters