Abstract: Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired temperature within a specified period of time to avoid the overshoot and absolute error, with better temperature tracking capability, else the process is disturbed.
To overcome above difficulties intelligent controllers, Fuzzy Logic (FL) and Adaptive Neuro-Fuzzy Inference System (ANFIS), are proposed in this paper. The Fuzzy controller is designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. To design ANFIS, Fuzzy-Inference-System is combined with learning capability of Neural-Network.
It is analyzed that ANFIS is best suitable for adaptive temperature control of above system. As compared to PID and FLC, ANFIS produces a stable control signal. It has much better temperature tracking capability with almost zero overshoot and minimum absolute error.
Abstract: A numerical study has been carried out to investigate
the heat transfer by natural convection of nanofluid taking Cu as
nanoparticles and the water as based fluid in a three dimensional
annulus enclosure filled with porous media (silica sand) between two
horizontal concentric cylinders with 12 annular fins of 2.4mm
thickness attached to the inner cylinder under steady state conditions.
The governing equations which used are continuity, momentum and
energy equations under an assumptions used Darcy law and
Boussinesq-s approximation which are transformed to dimensionless
equations. The finite difference approach is used to obtain all the
computational results using the MATLAB-7. The parameters affected
on the system are modified Rayleigh number (10 ≤Ra*≤ 1000), fin
length Hf (3, 7 and 11mm), radius ratio Rr (0.293, 0.365 and 0.435)
and the volume fraction(0 ≤ ¤ò ≤ 0 .35). It was found that the
average Nusselt number depends on (Ra*, Hf, Rr and φ). The results
show that, increasing of fin length decreases the heat transfer rate and
for low values of Ra*, decreasing Rr cause to decrease Nu while for
Ra*
greater than 100, decreasing Rr cause to increase Nu and adding
Cu nanoparticles with 0.35 volume fraction cause 27.9%
enhancement in heat transfer. A correlation for Nu in terms of Ra*,
Hf and φ, has been developed for inner hot cylinder.