Control of The Time Delay Systems Based on Elman Network and Smith Predictor  

Oleh:

Jie Tian ; Jie Chen ; Zhang, Yuhe ; Gong, Zhihao

Jenis: Article from Article
Dalam koleksi: Final Program and Book of Abstracts: The 4th Asian Control Conference, September 25-27, 2002 (Sep. 2002), page 642-646.
Topik: Control; Time Delay Systems; Elman Network; Smith Predictor
Fulltext: AC021297.PDF (317.06KB)

Isi artikel

Smith predictive control is theoretically a good solution to the problem of controlling the time delay systems. But it seldom gets use because it is almost impossible to find out a precise mathematical model of the practical system. In this paper, a mutually compensatory modeling method is discussed, in which the mechanism model simulates the main performance of the controlled process. As the mechanism model inevitably has modeling error more or less, a neural network can be used to model the modeling error of the mechanism model, and to compensate it. The simulation is performed following these ideas. The results prove that the Smith predictive control algorithm based on neural network compensatory model takes good advantages of nonlinear modeling capability of the neural network, and that the harm from the time delay to the performance and stability of the system can be counteracted completely if only the time delay is precisely known. Accordingly, with help of the neural network compensatory model, Smith predictor can be advanced to control the system whose mathematical model is difficult to precisely determined.

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