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Tytuł artykułu

Design of Intelligent PD Controller for Water Supply in Healthcare Systems

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Konferencja
International Conference on Information Technology and Knowledge Management (1 ; 22-23.12.2017 ; New Delhi, India)
Języki publikacji
EN
Abstrakty
EN
The necessity of clean environment is the major aspect in this modern age. This maintains a healthy environment. Also several trials have made with multidisciplinary researchers for development of healthy environment. However, it is even important to facilitate the unhealthy people in the healthcares. Some extent technology has an important role to support it. In this paper, a case study of water supply in the modern health care units is analyzed. This work describes the application of rule based Fuzzy Logic for control operation in water supply section. To refine fuzzy rules' initial approximate set automatically, a self-organizing fuzzy controller has been used. The quality factor is increased by applying the PD-type fuzzy controller. To make the system robust, the controller has been designed with Fuzzy Logic rules. The simulation results confirm the advantages and demonstrate for better dynamic behavior and performance, as well as perfect control with no overshoot. For low energy consumption, either the energy input is decreased or the efficiency of the mechanical transmission and processes has been increased. Performance of these new controllers has been verified through simulation using MATLAB.
Rocznik
Tom
Strony
93--96
Opis fizyczny
Bibliogr. 17 poz., rys.
Twórcy
  • Instrumentation & Electronics Engineering, College of Engineering, Bhubaneswar India
  • Electronics & Communication Engineering, ITER, Siksha 'O' Anusandhan Deemed to be University, Bhubaneswar, India
Bibliografia
  • 1. Sarangi, L., Mohanty, M. N., & Patnaik, S. (2017). Detection of abnormal cardiac condition using fuzzy inference system. International Journal of Automation and Control, 11(4), 372-383.
  • 2. Lokanath, S., Narayan, M. M., &Srikanta, P. (2016). Critical Heart Condition Analysis through Diagnostic Agent of e-Healthcare System using Spectral Domain Transform. Indian Journal of Science and Technology, 9(38).
  • 3. Sarangi, L., Mohanty, M. N., &Patnaik, S. (2016). Design of ANFIS Based E-Health Care System for Cardio Vascular Disease Detection. In Recent Developments in Intelligent Systems and Interactive Applications (pp. 445-453). Springer International Publishing.
  • 4. Lokanath Sarangi, Mihir Narayan Mohanty, SrikantaPattnaik, “An Intelligent Decision Support System for Cardiac Disease Detection”, IJCTA, International Press 2015.
  • 5. J. Yen, R. Langari: Fuzzy Logic: Intelligence, Control, and Information, Prentice-Hall, 1999.
  • 6. Y. S. Zhou, L. Y. Lai: Optimal Design for Fuzzy Controllers by Genetic Algorithms, IEEE Trans. On Industry Application, Vol. 36, No. 1, January/February 2000, pp. 93 – 97.
  • 7. Verbruggen, H. B. and Bruijn, P. M., 1997. Fuzzy control and conventional control: What is (And Can Be) the Real Contribution of Fuzzy Systems Fuzzy Sets Systems, Vol. 90, 151–160.
  • 8. Kowalska, T. O., Szabat, K. and Jaszczak, K., 2002. The Influence of Parameters and Structure of PI-Type Fuzzy-Logic Controller on DC Drive System Dynamics, Fuzzy Sets and Sysems, Vol. 131, 251-264.
  • 9. Ahmed, M. S., Bhatti, U. L., Al-Sunni, F. M. and El-Shafei, M., 2001. Design of a Fuzzy Servo-Controller, Fuzzy Sets and Systems, vol. 124: 231-247.
  • 10. Zilouchian, A., Juliano, M., Healy, T., 2000. Design of Fuzzy Logic Controller for a Jet Engine Fuel System, Control and Engineering Practices, Vol. 8: 873-883.
  • 11. Zadeh, L. A., 1965. Fuzzy sets, Information Control, Vol. 8, pp: 339-353.
  • 12. Liu, B. D., 1997. Design and Implementation of the Tree-Based Fuzzy Logic Controller, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics., Vol.27, No.3, 475-487.
  • 13. Zhiqiang, G., 2002. A Stable Self-Tuning Fuzzy Logic Control System for Industrial Temperature Regulation, IEEE 1886 Transactions on Industry Applications.Vol.38, No.2: 414-424.
  • 14. Shapiro, A. F., 2004. Fuzzy Logic in Insurance, Insurance: Mathematics and Economics, Vol.35, No.2 , 399-424.
  • 15. Hayward, G. and Davidson, V., 2003. Fuzzy Logic Applications, Analyst, Vol.128, 1304-1306.
  • 16. Peri, V. M. and Simon, D., 2005. Fuzzy Logic Control for an Autonomous Robot, North American Fuzzy Information Processing Society, NAFIPS 2005 Annual Meeting, 337- 342.
  • 17. SofianeAchiche, Wang Wei, Zhun Fan and others 2007: Genetically generated double-level fuzzy controller with a fuzzy adjustment strategy. GECCO’07, July 7-11
Uwagi
1. Preface
2. Technical Session: First International Conference on Information Technology and Knowledge Management
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3479eaed-55c6-4155-933a-a28dacf16f83
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