Performance Comparison of Level Control with the Three, Five & Nine Fuzzy Rules based method

Ashok Kumar, Rajbir ., Kuldeepak .


: In the previous paper we have discussed about the water level control in the ‘Three Non- Interacting Tank System’ with help of the Intelligent Fuzzy Controller over the classical method, in which we noticed that the performance of Classical method was very poor, system was slow i.e. response was slow and less accurate than that of Fuzzy Control system[1]. This paper discusses about comparing the performance of Intelligent Fuzzy Control system based on Three, Five and Nine Fuzzy rules. In that either comparing response of a single or interacting tank system with three rule based method, which gives better response, more accuracy than classical method. On the other hand, five rule based method is more complex and more accurate but system becomes slow than three rule based, because as increase in rule base makes system bulky more and more, but accuracy increase. Thus, nine rule based method makes system too bulky due to which system becomes very slow as compared to five and three rule based method but this system is more accurate than others. This paper provides information about complexity of system, performance and accuracy with different rule bases. The system’s overall performance will be optimum but it requires more practice, skill or experience. So, out of Three, Five and Nine rule method, the five rule system shows optimum behaviour.


Interacting Pair tank, MATLAB/ Simulink diagram, Conventional Controller.


“Level Control of a Three Tank Non-interacting System using Intelligent Controller”, Dr. Munish Vashishath: Associate Professor of Electronics Engg. In YMCAUST Faridabad, Ashok Kumar: M.Tech student in YMCAUST Faridabad & Kapil Dhama: Lecturer of ECE in SCET Palwal; WNTES-2012.

“Coupled Tank Systems”, Elke Laubwald, www.control-systems

“Performance Comparison between PID and Fuzzy Logic Controller in Level Control System of Twin Tank System”, Mohd Fua’ad Rahmat & Maraim MD Ghazaly, Journal Teknology, 45(D) Dis. 2006: 1-17.

“Robust MIMO Water Level Control in Interconnected Twin Tanks Using Second Order Sliding Mode Control”, M. Khan and S.K. Spurgeon, Control Engineering Practice VOL.14, Issue 4, April 2006, pp.375 – 386.

“Design & Simulation of Controller for Coupled Tanks System,” M. Mc Dermott & T. Brock, Control Engineering Practice VOL. 43, Issue 4, April 2009, pp.35-43.

“Design and application of Rough controller in three tank system”, Pan Aixian and Gao Yun, international conference on computing, control and industrial engineering, 2010.

“Analysis and Synthesis of fuzzy control system: A model based approach”. Feng G. CRC Press, p. 272, 2010.

“Introduction to Neural and Fuzzy Networks”, Dr. Erwin Sitompul, President University, lecture – 10, 11, 12, 2008.

“Fuzzy Controller- choosing an appropriate and smallest rule set”, Seema Chopra, R. Mitra and Vijay Kumar, international journal on computational cognition, dec2005.

“Analysis and Synthesis of Fuzzy Control System: A model based approach”, Feng G., CRC Press, p. 272, 2010.

“Design of Fuzzy Logic Controllers for Robust Process Control”, Yordanova S., King, S., 344,ISBN 987-954-9518-68-9, 2011.

Full Text: PDF


  • There are currently no refbacks.


All Rights Reserved © 2012 IJARCSEE

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.