Constrained robust predictive controller for uncertain processes modeled by orthonormal series functions
✍ Scribed by Gustavo H.C. Oliveira; Wagner C. Amaral; Gérard Favier; Guy A. Dumont
- Publisher
- Elsevier Science
- Year
- 2000
- Tongue
- English
- Weight
- 257 KB
- Volume
- 36
- Category
- Article
- ISSN
- 0005-1098
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✦ Synopsis
The present work focuses on robust predictive control (RPC) of uncertain processes and proposes a new approach based on orthonormal series function modeling. In such unstructured modeling, the output signal is described as a weighted sum of orthonormal functions that uses approximative information about the time constant of the process. Due to an e$cient uncertainty representation, this kind of modeling is advantageous in the RPC context, even for constrained systems and processes with integral action. The stability of the closed-loop system is guaranteed by the setting of su$cient conditions for the selection of the controller prediction horizon. Simulation results are presented to illustrate the performance of this new RPC algorithm.