Analysis and Design of a Three Inputs Fuzzy System for Maintaining the Cane Level during Sugar Manufacturing

Yogesh Misra^1, and H R Kamath²

¹Mewar University, Chittorgarh, Rajasthan, India

²Malwa Institute of Technology, Indore, Madhya Pradesh, India

Cite this paper:
Yogesh Misra and H R Kamath. Analysis and Design of a Three Inputs Fuzzy System for Maintaining the Cane Level during Sugar Manufacturing. Journal of Automation and Control. 2014; 2(3):62-78. doi: 10.12691/automation-2-3-2

Abstract

The amount of cane fiber carried by cane carrier in a sugar mill varies due to non-uniformity of cane supply. The continuous variation of cane in Donnelly chute during the cane juice extraction inversely affects the cane juice extraction efficiency of mill. This paper deals with the development of algorithm for a three input fuzzy controller with an aim to maintain the cane level in Donnelly chute during cane juice extraction. The developed controller generates the required rake carrier motor speed in rpm depending upon the value of cane level in Donnelly chute, quantity of cane on rake carrier and the roll speed. The three inputs fuzzy controller is developed and simulated for six cases by using fuzzy logic toolbox of ‘MATLAB^® version 7.11.0.584 (R2020b).

Keywords:
sugar mill cane carrier Donnelly chute juice extraction fuzzy algorithm fuzzy controller

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References:

[1]	D.P Kulkarni, Cane Sugar Manufacture, The sugar technologists association of India, New Delhi, 2002-03.
[2]	A Jha, “India’s sugar policy and world sugar economy” in proc. FAO International sugar conference, Fiji, August 2012.
[3]	Indian Sugar Mills Association (ISMA), 2010, “Important Events” (online) available at: http://www.indiansugar.com/EventDetails
[4]	S. Ahmed, Indian sugar industry, Centre for management studies, Jamia Millia Islamia, New Delhi, India, Unpublished.
[5]	Sugar Knowledge International Ltd., “How sugar is made”, (online) available at: http://www.sucrose.com/learn.html.
[6]	D.J Tayfield, P.W Rein and S.R Proome, “The application of a microprocessor based system for automatic pan boiling control”, Proc. The South African Sugar Technologists Association Conf; pp 56-62, June 1980.
[7]	C.R Murry, “The Pressure Required to Feed Cane Mills”. International Sugar Journal, 62, p. 346-349, 1960-61.
[8]	T. Ozkocak and G.C Goodwin, “A Nonlinear Modeling Approach to The Sugar Cane Crushing Process”. IEEE conference on Decision and Control, Florida, USAI.S.J., pp. 3144-3149, 1998.
[9]	T. Ozkocak, M. Fu and G.C Goodwin, “Maceration control of a sugar cane crushing mill”, Proc. American Control Conf; pp 2255-259, June 2000.
[10]	Misra, Y., Digital System Design using VHDL, Dhanpatrai & sons (P) Ltd., India, 2006.
[11]	Bhasker, J., A VHDL Primer, Revised Edition Prentice-Hall, 1992.
[12]	Brown, S., Vranesic, Z., Fundamentals of Digital Logic with VHDL Design, McGraw-Hill, 2000.
[13]	T Mitsuishi, N Endou and Y Sidhama, “The concept of fuzzy set and membership function and basic properties of fuzzy set operation” Journal of formalized mathematics, pp 1-6, Volume 12, 2003.
[14]	Mathworks, “Fuzzy Logic Toolbox User's Guide”, Mathworks, Inc., 2010.
[15]	R.M. Hilloowala and A.M. Sharaf, “A rule-based fuzzy logic controller for a PWM inverter in a standalone wind energy conversion scheme”, in Industry Applications, IEEE Transactions, pp. 57-65, January/February 1996.
[16]	L.Reznik, Fuzzy Controllers, Newnes-Butterworth-Heinemann, Oxford-Boston, 1997.
[17]	B Mahdad, T Bouktir and K Srairi, “Dynamic compensation of reactive energy usinf fuzzy controller” Leonardo Electronic Journal of practice and technologies, pp 1-16, Issue 7, July –December, 2005.