Based on the H∞ control technique and the strictly positive real Lyapunov (SPR-Lyapunov) design approach, an adaptive fuzzy-neural observer tuned on-line for a class of uncertain (unknown) nonlinear systems is developed. Unlike previous results, the assumption that the uncertain system nonlinearities only are restricted to the system output is not required. Moreover, the adaptive fuzzy-neural observer provides the modeling error (and the external bounded disturbance) attenuation with H∞ performance, obtained by a Riccati-like equation. Finally, simulation results demonstrate that the proposed observer yields satisfactory performance.
|Number of pages||6|
|Journal||Proceedings-IEEE International Conference on Robotics and Automation|
|Publication status||Published - 2000 Apr|
ASJC Scopus subject areas
- Control and Systems Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering