Design of Liquids Mixing Control System using Fuzzy Time Control Discrete Event Model for Industrial Applications
This paper presents a time control liquids mixing
system in the tanks as an application of fuzzy time control discrete
model. The system is designed for a wide range of industrial
applications. The simulation design of control system has three
inputs: volume, viscosity, and selection of product, along with the
three external control adjustments for the system calibration or to
take over the control of the system autonomously in local or
distributed environment. There are four controlling elements: rotatory
motor, grinding motor, heating and cooling units, and valves
selection, each with time frame limit. The system consists of three
controlled variables measurement through its sensing mechanism for
feed back control. This design also facilitates the liquids mixing
system to grind certain materials in tanks and mix with fluids under
required temperature controlled environment to achieve certain
viscous level. Design of: fuzzifier, inference engine, rule base,
deffuzifiers, and discrete event control system, is discussed. Time
control fuzzy rules are formulated, applied and tested using
MATLAB simulation for the system.
[1] M.Y. Hassan, Waleed F.Sharif. "Design of FPGA based PID-like Fuzzy
Controller for Industrial Applications", IAENG International Journal of
Computer Science, 34:2,IJCS_34-2-05.
[2] Shabiul Islam,Shakowat,"Development of a Fuzzy Logic Controller
Algorithm for Air-conditioning System", ICSE2006 Proc2006 IEEE.
[3] M.Saleem Khan,"Fuzzy Time Control Modeling of Discrete Event
Systems", ICIAR-51, WCECS 2008, pp.683-688.International
Conference on Intelligent Automation and Robotics. U.S.A.2008.
[4] Y.Y. Chen and T.C Tsao,"A description of the dynamic behaviour of
fuzzy systems", IEEE TransVol.19,July 1989, pp. 745-755.
[5] W. Pedryez, J.V. de Oliveia,"Optimization of Fuzzy Models", IEEE
Trans.Syst. Man, Cybern,Vol. 26, August. 1996, pp. 627-636.
[6] B. P. Zeigler, P. Herbert," Theory of Modeling and
Simulation,Integrating Discrete Event and Continuous Complex
Dynamic Systems" IEEE Press, 1994.
[7] M. Sugeno, Tanaka,"Successive identification of a fuzzy model and its
application to prediction of a complex system", fuzzy sets syst. Vol.
42,1991, pp. 315-334.
[8] Rolf Isermann, "On Fuzzy Logic Applications for Automatic
Control,Supervision, and Fault Diagnosis", IEEE Trans. On system, man
and cybernetics, vol. 28, NO.2 March 1998.
[1] M.Y. Hassan, Waleed F.Sharif. "Design of FPGA based PID-like Fuzzy
Controller for Industrial Applications", IAENG International Journal of
Computer Science, 34:2,IJCS_34-2-05.
[2] Shabiul Islam,Shakowat,"Development of a Fuzzy Logic Controller
Algorithm for Air-conditioning System", ICSE2006 Proc2006 IEEE.
[3] M.Saleem Khan,"Fuzzy Time Control Modeling of Discrete Event
Systems", ICIAR-51, WCECS 2008, pp.683-688.International
Conference on Intelligent Automation and Robotics. U.S.A.2008.
[4] Y.Y. Chen and T.C Tsao,"A description of the dynamic behaviour of
fuzzy systems", IEEE TransVol.19,July 1989, pp. 745-755.
[5] W. Pedryez, J.V. de Oliveia,"Optimization of Fuzzy Models", IEEE
Trans.Syst. Man, Cybern,Vol. 26, August. 1996, pp. 627-636.
[6] B. P. Zeigler, P. Herbert," Theory of Modeling and
Simulation,Integrating Discrete Event and Continuous Complex
Dynamic Systems" IEEE Press, 1994.
[7] M. Sugeno, Tanaka,"Successive identification of a fuzzy model and its
application to prediction of a complex system", fuzzy sets syst. Vol.
42,1991, pp. 315-334.
[8] Rolf Isermann, "On Fuzzy Logic Applications for Automatic
Control,Supervision, and Fault Diagnosis", IEEE Trans. On system, man
and cybernetics, vol. 28, NO.2 March 1998.
@article{"International Journal of Information, Control and Computer Sciences:49461", author = "M.Saleem Khan and Khaled Benkrid", title = "Design of Liquids Mixing Control System using Fuzzy Time Control Discrete Event Model for Industrial Applications", abstract = "This paper presents a time control liquids mixing
system in the tanks as an application of fuzzy time control discrete
model. The system is designed for a wide range of industrial
applications. The simulation design of control system has three
inputs: volume, viscosity, and selection of product, along with the
three external control adjustments for the system calibration or to
take over the control of the system autonomously in local or
distributed environment. There are four controlling elements: rotatory
motor, grinding motor, heating and cooling units, and valves
selection, each with time frame limit. The system consists of three
controlled variables measurement through its sensing mechanism for
feed back control. This design also facilitates the liquids mixing
system to grind certain materials in tanks and mix with fluids under
required temperature controlled environment to achieve certain
viscous level. Design of: fuzzifier, inference engine, rule base,
deffuzifiers, and discrete event control system, is discussed. Time
control fuzzy rules are formulated, applied and tested using
MATLAB simulation for the system.", keywords = "Fuzzy time control, industrial application and timecontrol systems, adjustment of Fuzzy system, liquids mixing system,design of fuzzy time control DEV system.", volume = "4", number = "12", pages = "1805-9", }