US 12,129,010 B2
Control system of damper of variable-air-volume air distributor and control method thereof
Guozeng Feng, Jiangsu (CN); Bo Meng, Jiangsu (CN); Guozhi Bao, Jiangsu (CN); Xinxin Gu, Jiangsu (CN); Chen Gu, Jiangsu (CN); and Tong Xu, Jiangsu (CN)
Assigned to Jiangsu university of science and technology, Jiangsu (CN)
Appl. No. 17/439,812
Filed by Jiangsu university of science and technology, Jiangsu (CN)
PCT Filed Mar. 23, 2021, PCT No. PCT/CN2021/082253
§ 371(c)(1), (2) Date Sep. 16, 2021,
PCT Pub. No. WO2022/062339, PCT Pub. Date Mar. 31, 2022.
Claims priority of application No. 202011011502.6 (CN), filed on Sep. 23, 2020.
Prior Publication US 2022/0306265 A1, Sep. 29, 2022
Int. Cl. F24F 11/755 (2018.01); B60H 1/00 (2006.01); B63J 2/04 (2006.01); F24F 11/63 (2018.01); F24F 110/10 (2018.01); F24F 110/40 (2018.01)
CPC B63J 2/04 (2013.01) [B60H 1/00792 (2013.01); B60H 1/00835 (2013.01); F24F 11/63 (2018.01); F24F 11/755 (2018.01); F24F 2110/10 (2018.01); F24F 2110/40 (2018.01)] 7 Claims
OG exemplary drawing
 
1. A control system of a damper of a variable-air-volume air distributor, comprising a volume adjusting valve for the variable-air-volume air distributor, a valve actuator, a BP (Back-Propagation) neural network-based main controller, a data collector and a user operation panel, wherein a signal of a set temperature of the user operation panel is connected to an input of the BP neural network-based main controller, the data collector collects room temperature and a static pressure at an inlet of the variable-air-volume air distributor, the collected data is connected to the input of the BP neural network-based main controller through different sensors, and an output of the BP neural network-based main controller is connected to an input of the valve actuator;
wherein the BP neural network-based main controller comprises a BP neural network predictive control module;
wherein the BP neural network predictive control module is a dual-input single-output module; and by setting two inputs of the BP neural network model for an opening action of the damper as a static pressure u and a demanded air volume v within an air duct, respectively, and one output as a valve opening y, the established mathematical model of the opening action of the damper is as follows:

OG Complex Work Unit Math
in formula (1), m is the number of neurons in the input layer, and k is the number of neurons in the output layer,

OG Complex Work Unit Math
the output value of the above model is continuously corrected by a negative gradient descent method, and the error function calculation formula is:
E(n)=Σk−1l½|rk(n)˜yk(n)|2  (2)
in formula (2), rk(n) is an expected output value, and yk(n) is an actual output value” or “wherein the control method comprises two functions: on-line modeling learning and off-line matching operating conditions, wherein the matched operating conditions are the prediction models constructed from sample data of the factory test, which are stored within the main controller after training and learning.