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Research Papers

Modeling and Simulation of an Electronic Oxygen Regulator Based on All-Coefficient Adaptive Control

[+] Author and Article Information
Yuxin Jiang

Intelligent Robots Key Laboratory,
College of Computer and Control Engineering,
Nankai University,
Tianjin 300071, China
e-mail: jiangyuxin@mail.nankai.edu.cn

Qinglin Sun

Professor
Intelligent Robots Key Laboratory,
College of Computer and Control Engineering,
Nankai University,
Tianjin 300071, China
e-mail: sunql@nankai.edu.cn

Panlong Tan

Intelligent Robots Key Laboratory,
College of Computer and Control Engineering,
Nankai University,
Tianjin 300071, China

Zengqiang Chen

Professor
Intelligent Robots Key Laboratory,
College of Computer and Control Engineering,
Nankai University,
Tianjin 300071, China

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received June 10, 2015; final manuscript received April 5, 2016; published online June 15, 2016. Assoc. Editor: Yongchun Fang.

J. Dyn. Sys., Meas., Control 138(8), 081010 (Jun 15, 2016) (7 pages) Paper No: DS-15-1267; doi: 10.1115/1.4033413 History: Received June 10, 2015; Revised April 05, 2016

Safe and reliable automatic pressure regulation of the oxygen mask is a primary consideration for the oxygen supply system. One kind of electronic oxygen regulator (EOR) structure is proposed, and its operation principle is explained in this paper. To avoid long controller design cycle, herein, some simulations are carried out on matlab for analysis by establishing a mathematical model according to the EOR flow dynamic characteristics. In the simulations, the all-coefficient adaptive control method based on a characteristic model (CM) and the proportional–integral–derivative (PID) algorithm are applied, and the results are thoroughly investigated by considering some disturbance, such as the user's changing pulmonary ventilation parameters, the air leakage of the mask, and the sensor noise. Results suggest that the all-coefficient control method is more effective to guarantee superior lower inspiratory resistance than the PID method with the environmental disturbance, which may be a plausible reference for the EOR controller design.

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References

Beaumont, M. , Lejeune, D. , Isabey, D. , Marotte, H. , Harf, A. , and Lofaso, F. , 1999, “ Positive Pressure Generation by Pneumatic and Electronic O2 Regulators: A Bench Experimental Evaluation,” Aviat. Space Environ. Med., 70(8), pp. 812–816. [PubMed]
Zeng, Y. , Du, C. H. , Zhou, Y. , and Lan, Y. Q. , 2013, “ Design of Electronic Aviation Oxygen Regulator Structure,” Appl. Mech. Mater., 421, pp. 150–156. [CrossRef]
Sun, C. F. , Cai, Y. Y. , and Long, H. J. , 2013, “ Research on Stepping Motor Fuzzy Control Technology Application in the Aircraft Electronic Oxygen Regulator,” Meas. Control Technol., 32(4), pp. 78–81 (in Chinese).
“Oxygen and Anti-G Regulator for F-35.”
Ziegler, J. G. , and Nichols, N. B. , 1942, “ Optimal Settings for Automatic Controllers,” Trans. ASME, 64, pp. 759–768.
Astrom, K. J. , and Hagglund, T. , 1996, PID Control, CRC and IEEE Press, Boca Raton, FL.
Yang, B. , Peng, J. H. , Guo, S. H. , Zhang, S. M. , Li, W. , and He, T. , 2012, “ Acid-Pickling Plates and Strips Speed Control System by Microwave Heating Based on Self-Adaptive Fuzzy PID Algorithm,” J. Cent. South Univ., 19(8), pp. 2179–2186. [CrossRef]
Wu, H. X. , Xie, Y. C. , Li, Z. Y. , and He, Y. Z. , 1999, “ Intelligent Control Based on Description of Plant Characteristic Model,” Acta Autom. Sin., 25(1), pp. 9–17 (in Chinese).
Wu, H. X. , Liu, Y. W. , Liu, Z. H. , and Xie, Y. C. , 2001, “ Characteristic Modeling and the Control of Flexible Structure,” Sci. China Ser.: Inf. Sci., 44(4), pp. 278–291.
Meng, B. , and Wu, H. X. , 2007, “ A Unified Proof of the Characteristic Model of Linear Time-Invariant Systems,” American Control Conference, IEEE, New York, July 9–13, pp. 935–940.
Wang, Y. , 2012, “ Stability Analysis of Characteristic Model Based All-Coefficient Adaptive Control for a Class of Minimum-Phase Linear System,” Procedia Eng., 29, pp. 2410–2420. [CrossRef]
Huang, H. , 2015, “ Multiple Characteristic Model-Based Golden-Section Adaptive Control: Stability and Optimization,” Int. J. Adapt. Control Signal Process., 29(7), pp. 877–904. [CrossRef]
Wu, H. X. , Wang, Y. C. , and Xing, Y. , 2003, “ Intelligent Control Based on Intelligent Characteristic Model and Its Application,” Sci. China, Ser. F: Inf. Sci., 46(3), pp. 225–240. [CrossRef]
Wu, H. X. , Hu, J. , and Xie, Y. C. , 2007, “ Characteristic Model-Based All-Coefficient Adaptive Control Method and Its Applications,” IEEE Trans. Syst., Man, Cybern., Part C: Appl. Rev., 37(2), pp. 213–221. [CrossRef]
Meng, B. , Wu, H. X. , Lin, Z. L. , and Li, G. , 2009, “ Characteristic Model Based Control of the X-34 Reusable Launch Vehicle in Its Climbing Phase,” Sci. China, Ser. F: Inf. Sci., 52(11), pp. 2216–2225. [CrossRef]
Meng, B. , and Wu, H. X. , 2010, “ On Characteristic Modeling of a Class of Flight Vehicles' Attitude Dynamics,” Sci. China: Technol. Sci., 53(8), pp. 2074–2080. [CrossRef]
Gao, S. G. , Dong, H. R. , and Ning, B. , 2014, “ Characteristic Model-Based All-Coefficient Adaptive Control for Automatic Train Control Systems,” Sci. China Inf. Sci., 57(9), pp. 1–12. [CrossRef]
Di, L. , and Lin, Z. L. , 2014, “ Control of a Flexible Rotor Active Magnetic Bearing Test Rig: A Characteristic Model Based All-Coefficient Adaptive Control Approach,” Control Theory Technol., 12(1), pp. 1–12. [CrossRef]
GJB, 1990, “ Physiological Requirements for Aircraft Positive Pressure Oxygen,” China National Military Standard, Standard No. GJB 867-90 (in Chinese).
GJB, 1991, “ Acceptable Levels for Breathing Resistance of Aircraft Oxygen Equipment,” China National Military Standard, Standard No. GJB 1013-90 (in Chinese).
White, F. M. , 2011, Fluid Mechanics, 7th ed., McGraw-Hill, New York.
Wu, H. X. , Hu, J. , and Xie, Y. C. , 2009, Characteristic Model-Based Intelligent Adaptive Control, China Science and Technology Press, Beijing, China.
GJB, 1987, “ Pilot's Parameters of Pulmonary Ventilation During Flight,” China National Military Standard, Standard No. GJB 305-87 (in Chinese).

Figures

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Fig. 1

Schematic diagram of oxygen supply system

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Fig. 2

Block diagram of the plant model

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Fig. 3

Feedback block diagram of all-coefficient control method

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Fig. 4

Outputs of the oxygen regulator and CM with the same inputs

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Fig. 5

The coefficient identification

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Fig. 6

Simulation result with constant pulmonary ventilation

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Fig. 7

Simulation result with changing pulmonary ventilation

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Fig. 8

Simulation result with air leakage based on CM-based all-coefficient controller

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Fig. 9

Simulation result with air leakage based on PID controller

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Fig. 10

Simulation result with sensor noise

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Fig. 11

The close-up result

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