Fuzzy-adaptive decentralized output-feedback control for large-scale nonlinear systems with dynamical uncertainties

  • Authors:

  • Shaocheng Tong;Changliang Liu;Yongming Li

  • Affiliations:

  • Department of Mathematics, Liaoning University of Technology, Jinzhou, Liaoning, China;Department of Mathematics, Liaoning University of Technology, Jinzhou, Liaoning, China;Department of Mathematics, Liaoning University of Technology, Jinzhou, Liaoning, China

  • Venue:
  • IEEE Transactions on Fuzzy Systems
  • Year:
  • 2010

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Abstract

In this paper, an adaptive fuzzy-decentralized robust output-feedback-control approach is proposed for a class of large-scale strict-feedback nonlinear systems with the unmeasured states. The large-scale nonlinear systems in this paper are assumed to possess the unstructured uncertainties, unmodeled dynamics, and unknown high-frequency-gain sign. Fuzzy-logic systems are used to approximate the unstructured uncertainties, K-filters are designed to estimate the unmeasured states, and a dynamical signal and a special Nussbaum gain function are introduced into the control design to solve the problem of unknown high-frequency-gain sign and dominate unmodeled uncertainties, respectively. Based on the backstepping design and adaptive fuzzy-control methods, an adaptive fuzzy-decentralized robust output-feedback-control scheme is developed. It is proved that the proposed adaptive fuzzy-control approach can guarantee that all the signals in the closed-loop system are uniformly and ultimately bounded, and the tracking errors converge to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by using simulation results.