Abstract
A decentralized adaptive output feedback control design is proposed for large-scale interconnected systems. It is assumed that all the controllers share prior information about the system reference models. Based on that information, a linearly parameterized neural network is introduced for each subsystem to partially cancel the effect of the interconnections on the tracking performance. Boundedness of error signals is shown through Lyapunov's direct method.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1699-1704 |
| Number of pages | 6 |
| Journal | Proceedings of the IEEE Conference on Decision and Control |
| Volume | 2 |
| State | Published - Dec 1 2003 |
| Externally published | Yes |
| Event | 42nd IEEE Conference on Decision and Control - Maui, HI, United States Duration: Dec 9 2003 → Dec 12 2003 |
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ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization
Cite this
Hovakimyan, N., Lavretsky, E., Calise, A. J., & Sattigeri, R. (2003). Decentralized Adaptive Output Feedback Control via Input/Output Inversion. Proceedings of the IEEE Conference on Decision and Control, 2, 1699-1704.