Abstract
This paper presents a method for designing an H∞-observer-based adaptive fuzzy-neural output feedback control law with on-line tuning of fuzzy-neural weighting factors for a class of uncertain nonlinear systems based on the H∞ control technique and the strictly positive real Lyapunov (SPR-Lyapunov) design approach. The H∞-observer-based output feedback control law guarantees all signals involved are bounded, and provides the modeling error (and the external bounded disturbance) attenuation with H∞ performance, obtained by a Riccati-like equation. Besides, the H∞-observer-based output feedback control law doesn't require the assumptions of the total system states available for measurement and the uncertain system nonlinearities only restricted to the system output. Finally, an example is simulated in order to confirm the effectiveness and applicability of the proposed methods.
| Original language | English |
|---|---|
| Pages (from-to) | I-449 - I-454 |
| Journal | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
| Volume | 1 |
| Publication status | Published - 1999 |
| Externally published | Yes |
| Event | 1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Jpn Duration: 1999 Oct 12 → 1999 Oct 15 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Hardware and Architecture