Comparative study of temperature control in a heat exchanger process

Dissertant

al-Tae, Afra Hilal Kamil

Thesis advisor

al-Nuaymi, Safa al-Din Abd Allah

University

University of Technology

Faculty

-

Department

Department of Chemical Engineering

University Country

Iraq

Degree

Master

Degree Date

2011

English Abstract

-In this work the dynamic behavior of a plate heat exchanger (PHE) (single pass counter current consists of 24 plates) both experimentally and theoretically and the control of the system were studied.

Different control strategies; conventional feedback control, classical fuzzy logic control, artificial neural network (NARMAL2) control and PID fuzzy control were used to control the outlet cold water temperature.

A step change is carried in the hot water flow rate which is considered as a manipulated variable.

The experimental heat transfer measurements of the PHE show that the overall heat transfer coefficient (U) is related to the hot water flow rate (mh) by a correlation having the form: U mh 0.7158 =11045 In this work the PHE model is found dynamically as a first order lead and second order overdamped lag while the experimental PHE represented dynamically as a first order with negligible dead time value.

A comparison between the experimental and the theoretical model is carried out and good agreement is obtained.

The response of 24 plates when justifying the design fitness of the PHE, proved that the design is accurate and there are no losses in the energy input.

The performance criteria used for different control modes are the integral square error (ISE) and integral time-weighted absolute error (ITAE) where the ITAE gave better performance.

As well as the parameters of the step performance of the system such as overshoot value, settling time and rise time are used to evaluate the performance of different control strategies.

The tuning of control parameters were determined for PI and PID controllers by two different methods; Ziegler-Nichols (Bode diagram), and Cohen-Coon (process reaction curve) to find the best values of proportional gain (Kc), integral time (τ I) and derivative time (τD).

Accurate results have been obtained using artificial neural network over PI, PID and classical fuzzy logic controller.

The PID fuzzy controller gave better control results of temperature rather than PI, PID, classical fuzzy logic and artificial neural network controller because PID fuzzy controller combines the advantages of a fuzzy logic controller and a PID controller.

The best value of settling time and overshoot were found of 0.432 and 1.0 respectively which represent the PID fuzzy controller, while the best rise time found of 0.077 which represent the PID controller.

The lower value of ITAE of 0.0031 is obtained which represent the PID fuzzy controller and to certain the best strategy of control among the others.

MATLAB program version 7.10 was used as a tool of simulation for all the studies mentioned in this work.

Keywords : heat exchanger .

dynamic .

model .

PI control .

PID control .

fuzzy control .

artificial neural network control .

PID fuzzy control.

Main Subjects

Physics

Topics

• Thermodynamics

• APA
• MLA
• AMA

Language

English

Data Type

Arab Theses

Record ID

BIM-305108