Comparison of Proportional Control and Fuzzy Logic Control to Develop an Ideal Thermoelectric Renal Hypothermia System
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Comparison of Proportional Control and Fuzzy Logic Control to Develop an Ideal Thermoelectric Renal Hypothermia System

Authors: Hakan Işık, Esra Saraçoğlu

Abstract:

In this study, a comparison of two control methods, Proportional Control (PC) and Fuzzy Logic Control (FLC), which have been used to develop an ideal thermoelectric renal hypothermia system in order to use in renal surgery, has been carried out. Since the most important issues in long-lasting parenchymatous renal surgery are to provide an operation medium free of blood and to prevent renal dysfunction in the postoperative period, control of the temperature has become very important in renal surgery. The final product is seriously affected from the changes in temperature, therefore, it is necessary to reach some desired temperature points quickly and avoid large overshoot. PIC16F877 microcontroller has been used as controller for both of these two methods. Each control method can simply ensure extra renal hypothermia in the targeted way. But investigation of advantages and disadvantages of every control method to each other is aimed and carried out by the experimental implementations. Shortly, investigation of the most appropriate method to use for development of system and that can be applied to people safely in the future, has been performed. In this sense, experimental results show that fuzzy logic control gives out more reliable responses and efficient performance.

Keywords: renal hypothermia, renal cooling, temperature control, proportional control fuzzy logic control

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1085078

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References:


[1] Laven, B.A.; Kasza K.E.; Rapp D.E.; Orvieto M. A.; Lyon M.B.; Oras J.J.; Beisert D. G.; Hoekt T.L.V.; Son H.; Shalhav A.L. A pilot study of ice-slurry application for inducing laparoscopic renal hypothermia, BJU International. 2006, 99 (1), 166-170.
[2] Işık, H.; Sert, U.; Yavru, N.; Allahverdi, N. Microcontroller Based Hypothermia System. Proceedings of the International Conference on Computer Systems and Technologies-CompSysTech-07, June 14 - 15, Rousse, Bulgaria , 2007
[3] Ramani, A.P.; Ryndin, I.; Lynch, A.C.; Veetil, R.T.P. Current concepts in achieving renal hypothermia during laparoscopic partial nephrectomy. Brit. J. Urol. Intl. 2006,97 (2), 342-344.
[4] Is─▒k, H. A New Microcontroller Supervised Thermoelectric Renal Hypothermia System. J. Med. Syst. 2005, 29 (5), 1-10.
[5] Lin, C.J. A GA-based neural fuzzy system for temperature control, Fuzzy Sets and Systems. 2004, 143 (2), 311-333.
[6] Wilkinson, J. Additional Advances in Fuzzy Logic Temperature Control Conf. Record of the 1995 IEEE Ind. Applic. Conf. 1995, 3, 2721-2725.
[7] Ward, J.P. Determination of the optimal temperature for regional renal hypothermia during temporary renal ischemia. Brit. J. Urol. 1975, 47, 17-24.
[8] Cockett, A.T.;The kidney and regional hypothermia. Surgery. 1961, 50, 905-910.
[9] Wakabayashi, Y.; Narita, M.; Kim, C.J. Renal hypothermia using ice slush for retroperitoneal laparoscopic partial nephrectomy. Urology. 2004, 63, 773-775.
[10] Yasin, F. M.; Tio, A.; Islam, M.S.; Reaz, M. I.; Suleiman, M.S. The Hardware Design of Temperature Controller Based on Fuzzy Logic for Industrial Application, Employing FPGA. Microelectronics 2004, ICM 2004 Proceedings. The 16th International Conference on, IEEE, 2004, 157-160.
[11] Ogata K. Modern Control Engineering; 3rd ed. Prentice - Hall Inc: Upper Saddle River, New Jersey, 1997; 215 pp.
[12] Zhiqiang, G.; Trautzsch, T.A.; Dawson, J.G. A stable self-tuning fuzzy logic control system for industrial temperature regulation. IEEE Ind. Applic. Conf. 2001, 2, 1232 - 1240.
[13] Li, X.; Shen, H.W. Adaptive volume rendering using fuzzy logic control. Proceeding of Joint Eurographics - IEEE TCVG symposium on visualization, Springer, Berlin, 2001.
[14] Kim, S. C.; Seo, H. W.; Han, H. S.; Khatib, O. Fuzzy Logic Control of A Robot Manipulator Based on Visual Servoing. Industrial Electronics, 2001.Proceedings. ISIE 2001. IEEE International Symposium on, June 12-16, 2001, 3,1597 - 1602.
[15] Is─▒k, H.; Saracoglu, E; Guler, I. Design of Fuzzy Logic Controlled Thermoelectric Renal Hypothermia System. Instrumentation Science & Technology. 2008, 36(1), 310 - 322.