Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control

663 Ogledov
827 Prenosov
Izvoz citacije: ABNT
YI, Jiangang .
Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 61, n.2, p. 115-122, june 2018. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/sl/article/modelling-and-analysis-of-step-response-test-for-hydraulic-automatic-gauge-control/>. Date accessed: 06 dec. 2019. 
doi:http://dx.doi.org/10.5545/sv-jme.2014.2046.
Yi, J.
(2015).
Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control.
Strojniški vestnik - Journal of Mechanical Engineering, 61(2), 115-122.
doi:http://dx.doi.org/10.5545/sv-jme.2014.2046
@article{sv-jmesv-jme.2014.2046,
	author = {Jiangang  Yi},
	title = {Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {61},
	number = {2},
	year = {2015},
	keywords = {Step Response; HAGC; PID; Artificial Neural Networks},
	abstract = {The step response for hydraulic automatic gauge control (HAGC) determines the steel rolling speed and the steel sheet thickness in the process of rolling production. In this paper, the step response test process of HAGC was analysed, and a test approach was proposed for it. Based on that, the transfer function model of the step response test was established and simulated by using Matlab. In order to reduce the settling time and the overshoot, an adaptive proportional-integral-derivative (APID) link was presented in order to compensate for the input signal by using back propagation neural networks (BPNN). The experimental results show that the improved step response test model reaches the process requirements of HAGC, eliminates the jitter of the HAGC system at the start-up phase, and has better stability as well as faster response for steel sheet rolling.},
	issn = {0039-2480},	pages = {115-122},	doi = {10.5545/sv-jme.2014.2046},
	url = {https://www.sv-jme.eu/sl/article/modelling-and-analysis-of-step-response-test-for-hydraulic-automatic-gauge-control/}
}
Yi, J.
2015 June 61. Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 61:2
%A Yi, Jiangang 
%D 2015
%T Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control
%B 2015
%9 Step Response; HAGC; PID; Artificial Neural Networks
%! Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control
%K Step Response; HAGC; PID; Artificial Neural Networks
%X The step response for hydraulic automatic gauge control (HAGC) determines the steel rolling speed and the steel sheet thickness in the process of rolling production. In this paper, the step response test process of HAGC was analysed, and a test approach was proposed for it. Based on that, the transfer function model of the step response test was established and simulated by using Matlab. In order to reduce the settling time and the overshoot, an adaptive proportional-integral-derivative (APID) link was presented in order to compensate for the input signal by using back propagation neural networks (BPNN). The experimental results show that the improved step response test model reaches the process requirements of HAGC, eliminates the jitter of the HAGC system at the start-up phase, and has better stability as well as faster response for steel sheet rolling.
%U https://www.sv-jme.eu/sl/article/modelling-and-analysis-of-step-response-test-for-hydraulic-automatic-gauge-control/
%0 Journal Article
%R 10.5545/sv-jme.2014.2046
%& 115
%P 8
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 61
%N 2
%@ 0039-2480
%8 2018-06-27
%7 2018-06-27
Yi, Jiangang.
"Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control." Strojniški vestnik - Journal of Mechanical Engineering [Online], 61.2 (2015): 115-122. Web.  06 Dec. 2019
TY  - JOUR
AU  - Yi, Jiangang 
PY  - 2015
TI  - Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2014.2046
KW  - Step Response; HAGC; PID; Artificial Neural Networks
N2  - The step response for hydraulic automatic gauge control (HAGC) determines the steel rolling speed and the steel sheet thickness in the process of rolling production. In this paper, the step response test process of HAGC was analysed, and a test approach was proposed for it. Based on that, the transfer function model of the step response test was established and simulated by using Matlab. In order to reduce the settling time and the overshoot, an adaptive proportional-integral-derivative (APID) link was presented in order to compensate for the input signal by using back propagation neural networks (BPNN). The experimental results show that the improved step response test model reaches the process requirements of HAGC, eliminates the jitter of the HAGC system at the start-up phase, and has better stability as well as faster response for steel sheet rolling.
UR  - https://www.sv-jme.eu/sl/article/modelling-and-analysis-of-step-response-test-for-hydraulic-automatic-gauge-control/
@article{{sv-jme}{sv-jme.2014.2046},
	author = {Yi, J.},
	title = {Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {61},
	number = {2},
	year = {2015},
	doi = {10.5545/sv-jme.2014.2046},
	url = {https://www.sv-jme.eu/sl/article/modelling-and-analysis-of-step-response-test-for-hydraulic-automatic-gauge-control/}
}
TY  - JOUR
AU  - Yi, Jiangang 
PY  - 2018/06/27
TI  - Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 61, No 2 (2015): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2014.2046
KW  - Step Response, HAGC, PID, Artificial Neural Networks
N2  - The step response for hydraulic automatic gauge control (HAGC) determines the steel rolling speed and the steel sheet thickness in the process of rolling production. In this paper, the step response test process of HAGC was analysed, and a test approach was proposed for it. Based on that, the transfer function model of the step response test was established and simulated by using Matlab. In order to reduce the settling time and the overshoot, an adaptive proportional-integral-derivative (APID) link was presented in order to compensate for the input signal by using back propagation neural networks (BPNN). The experimental results show that the improved step response test model reaches the process requirements of HAGC, eliminates the jitter of the HAGC system at the start-up phase, and has better stability as well as faster response for steel sheet rolling.
UR  - https://www.sv-jme.eu/sl/article/modelling-and-analysis-of-step-response-test-for-hydraulic-automatic-gauge-control/
Yi, Jiangang"Modelling and Analysis of Step Response Test for Hydraulic Automatic Gauge Control" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 61 Number 2 (27 June 2018)

Avtorji

Inštitucije

  • Jianghan University, Hubei Key Laboratory of Industrial Fume & Dust Pollution Control, Wuhan, China 1

Informacije o papirju

Strojniški vestnik - Journal of Mechanical Engineering 61(2015)2, 115-122

https://doi.org/10.5545/sv-jme.2014.2046

The step response for hydraulic automatic gauge control (HAGC) determines the steel rolling speed and the steel sheet thickness in the process of rolling production. In this paper, the step response test process of HAGC was analysed, and a test approach was proposed for it. Based on that, the transfer function model of the step response test was established and simulated by using Matlab. In order to reduce the settling time and the overshoot, an adaptive proportional-integral-derivative (APID) link was presented in order to compensate for the input signal by using back propagation neural networks (BPNN). The experimental results show that the improved step response test model reaches the process requirements of HAGC, eliminates the jitter of the HAGC system at the start-up phase, and has better stability as well as faster response for steel sheet rolling.

Step Response; HAGC; PID; Artificial Neural Networks