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Tytuł artykułu

Heating control of heated twin radiosonde humidity sensor based on DMC

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In order to effectively solve condensation and icing problems of radiosonde in low-temperature environment at high altitude, humidity sensor heated automatic alternately to remove pollution and improve the measurement accuracy. Heat experiments obtained the curve of rising temperature and responsible time on heated twin humidity sensor in normal temperature and pressure, by expanded responsible curve to obtain heated model of twin heated humidity sensor and by the analysis of heating model, use DMC and PID control for heating respectively. Simulation results show that the DMC control meets the practical requirements of measure at high altitude.
Rocznik
Tom
S 1
Strony
52--58
Opis fizyczny
Bibliogr. 29 poz., rys.
Twórcy
autor
  • Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • School of Information and Control. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China
autor
  • Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • School of Information and Control. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China
autor
  • Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China
autor
  • Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China
autor
  • Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China
Bibliografia
  • 1. Wei, Zhao Peitao, Guo Qiyun, et al. 2011. The international radiosonde intercomparison results for China-made GPS radiosonde. Journal of Applied Meteorology (in Chinese), 22(4):453–462
  • 2. Ye X l, Liao J l , Gao , D X , Wang F F .based on PSO support vector machine humidity sensor temperature compensation [J] Instrument Technique and Sensor, 2013 (11): 14-30.
  • 3. Liu Q Q,Dai W,Yang R K,et al. Fluid dynamics analysis on solar radiation error of radiosonde temperature measurement. Plateau Meteorology,2013; 32( 4) : 1157—1164
  • 4. Ciesielski P E,Johnson R H,Wang J H. Correction of humidity biases in Vaisala RS80-H sondes during NAME. Journal of Atmospheric and Oceanic Technology,2009; 26: 1763—1780
  • 5. Indrajit Mukherjee,Srikanta Routroy, Comparing the Performance of Neural Networks Developed by Using Levenberg-Marquardt and Quasi-Newton with the Gradient Descent Algorithm for Modelling a Multiple Response Grinding Process [J] Expert Systems with Applications,2012( 39) : 2397 - 2407
  • 6. Stuart Bennett. The past of PID controllers[J]. Annual Reviews in Control, 2001, 25: 43-53.
  • 7. I. Cervantesa, J. Alvarez-Ramirezb. On the PID tracking control of robot manipulators. Systems and Control Letter,vol. 42, no. 1, pp. 37–46, 2001.
  • 8. KAYA I. IMC based automatic tuning method for PID controllers in a Smith predictor configuration [J]. Computers and Chemical Engineering, 2004, 28(3): 281−290.
  • 9. HAN J Q. Form PID to active disturbance rejection control [J]. IEEE Transaction on Industrial Electronics, 2009, 56(3): 900−906.
  • 10. ASTROM K J, HAGGLUND T. The future of PID control [J]. Control Engineering Practice, 2001, 9: 1163−1175.
  • 11. LI Y, KIAM H A, GREGORY C Y. Patents, software and hardware for PID Control [J]. IEEE Control Systems Magazine, 2006, 26(1): 42−54.
  • 12. LI H X, GATLAND B H, GREEN A W. Fuzzy variable structure control [J]. IEEE Trans Sys, Man, Cybern B, 1997, 27(2): 306− 312.
  • 13. Zadeh L. Fuzzy Sets[J]. Journal of Information and Control, 1965, 8: 338-353.
  • 14. L. Peng, P. Y. Woo. Neural-fuzzy control system for robotic manipulators. IEEE Control Systems Magazine, vol. 22,no. 1, pp. 53–63, 2006.
  • 15. H. F. Ho, Y. K. Wong, A. B. Rad. Robust fuzzy tracking control for robotic manipulators. Simulation Modeling Practice and Theory, vol. 15, no. 7, pp. 801–816, 2007.
  • 16. Z. J. Sun, R. T. Xing, C. S. Zhao, W. Q. Huang. Fuzzy auto-tuning PID control of multiple joint robot driven by ultrasonic motors. Ultrasonics, vol. 46, no. 4, pp. 303–312, 2007.
  • 17. Simminger J,Peterson T.Constrained multivariable nonlinear model predictive control based on iterative QDMC.IFAC advanced control of chemical processes,To ulonse,France,1991,1: 149-154.
  • 18. Liuyou Fei, Wu Gang, Wei Heng Hua, Sun Demin stepped Dynamic Matrix Control and Its Application in Temperature Control System [J] University of Science and Technology of China, 2005 (6): 347-352.
  • 19. Wang Shihu,Shen Jiong,Li Yiguo. Multi-model control method and research progress [J] Industrial instrumentation and Automation,2008,(1) : 13-17
  • 20. Abderrahim A.Dynamic matrix control(DMC) of rolling mills[J].Mterials and manufacturing processes,2007,22(7):909-915.
  • 21. Zhou J.Z,Li X,Zhu H.T.Application and simulation of DMC controller in time delay inertial system[C].2008 Chinese control and decision conference,2008:640-654.
  • 22. NOAA, NASA, USAF, et al. U. S. Standard Atmosphere[M]. Washington, D. C. :U. S. Government Printing Office, 1976:53-63.
  • 23. Bhajneet Singh, Sukanta K. Dash. Natural convection heat transfer from a finned sphere[J]. International Journal of Heat and Mass Transfer. 2015,81(2):305-324.
  • 24. Y.Y. Qiu, C. Azeredo-Leme, L.R. Alcacer, et al. A CMOS humidity sensor with on-chip calibration[J]. Sensors andActuatorsA. 2001, 92:80-87.
  • 25. Kalyan Phani Tangirala, J. Robert Heath, Arthur Radun. A Handheld Programmable-Logic-Device-Based Temperature and Relative-Humidity Senso, Processor, and Display System Platform forAutomation and Control of Industry Process [J]. 2010, 46(4):1619-1629.
  • 26. Elbisy, MS. Sea Wave Parameters Prediction by Support Vector Machine Using a Genetic Algorithm [J]. Journal of Coastal Research. 2015, 31(4): 892-899.
  • 27. Gu .L, Qin.M,Huang .Q.A, CMOS integrated capacitive humidity sensor [J] Instrument Technique and Sensor, 2003, (06): 7-11.
  • 28. Watson, PJ. Development of a Unique Synthetic Data Set to Improve Sea-Level Research and Understanding [J]. Journal of Coastal Research. 2015, 3(3): 758-770.
  • 29. Liu .Q.Q, Yang .J, Yang R.K and other dual heating humidity sensor CFD Analysis and Design of heating strategies [J] Sensing Technology, 201 225 (08): 1039-1044.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fab5373a-94a6-449d-9664-25565e8f8249
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