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A Novel Robust Predictive Control System Over Imperfect Networks.
- Source :
- IEEE Transactions on Industrial Electronics; Feb2017, Vol. 64 Issue 2, p1751-1761, 11p
- Publication Year :
- 2017
-
Abstract
- This paper aims to study on feedback control for a networked system with both uncertain delays and, packet dropouts and disturbances. Here, a so-called robust predictive control (RPC) approach is designed as follows: 1) delays and packet dropouts are accurately detected online by a network problem detector; 2) a so-called proportional-integral-based neural network grey model (PINNGM) is developed in a general form to be capable of forecasting accurately in advance the network problems and the effects of disturbances on the system performance; 3) using the PINNGM outputs, a small adaptive buffer (SAB) is optimally generated on the remote side to deal with the large delays and/or packet dropouts and, therefore, simplify the control design; 4) based on the PINNGM and SAB, an adaptive sampling-based integral state feedback controller is simply constructed to compensate the small delays and disturbances. Thus, the steady-state control performance is achieved with fast response, high adaptability, and robustness. Case studies are finally provided to evaluate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02780046
- Volume :
- 64
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Industrial Electronics
- Publication Type :
- Academic Journal
- Accession number :
- 120763747
- Full Text :
- https://doi.org/10.1109/TIE.2016.2580124