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Real-time control of AHU based on a neural network assisted cascade control system

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3 Author(s)
Chengyi Guo ; Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore ; Qing Song ; Wenjian Cai

In this paper, we propose a novel neural network assisted proportional-plus-integral (PI) control strategy to improve the supply air pressure control performance of variable air volume (VAV) system. The neural network is trained on-line with a normalized training algorithm, which eliminates the requirement of a bounded regression signal to the system. To ensure the convergence of the training algorithm, an adaptive dead-zone scheme is employed. Stability of the proposed control scheme is guaranteed based on the conic sector theory. To demonstrate the applicability of the proposed method, real-time tests were carried out on a pilot VAV air-conditioning system and good experimental results were obtained.

Published in:

Robotics, Automation and Mechatronics, 2004 IEEE Conference on  (Volume:2 )

Date of Conference:

1-3 Dec. 2004