Journal of control & instrumentation (vol5, issue2) by STM Journals Publication

ISSN : 2347 - 7237

Journal of Jan - April 2014

Control & Instrumentation (JoCI) May - August 2014

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Dr. Dipak Adhyaru Professor and Head, Instrumentation and Control Engineering Dept., Nirma University,Ahmedabad, Gujarat, India.

Dr. Ketan Pravinchandra Assistant Professor, Department of Electrical Engineering, Indian Institute of Technology Hyderabad, Yeddumailaram, Andhra Pradesh, India.

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Dr. M V. Vaidyan Professor, Department of Electrical Engineering, National Institute of Technology Calicut, Kerala , India.

M Manimaran Scientific officer, IGCAR, Kanchipuram, Tamil Nadu, India.

Dr. Chandar Ts Professor and Head, Dept. of Electronics and Communication, PES Institute of Technology, Bangalore, India.

Dr. Sabura Banu Professor, Dept. of Electronics and Instrumentation Engineering, B.S. Abdur Rahman University, Vandalur, Chennai, India.

Dr. J. Mohanalin Raja Rathnam Professor, St. Joseph's College of Engineering and Technology, Palai, India.

Dr. Kiran Chakravarthula Associate Professor, Dept. of Electronics &Instrumentation Engineering, V.N.R. Vignana Jyothi Institute of Engineering & Technology, Hyderabad, India.

Dr. Santhosh K. V. Assistant Professor, Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal India.

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STM JOURNALS

I take the privilege to present the hard copy compilation for the [Volume 5 Issue (2)] of Journal of Control & Instrumentation. The intension of JoCI is to create an atmosphere that stimulates creativeness, research and growth in the area of Control & Instrumentation. The development and growth of the mankind is the consequence of brilliant Research done by eminent Scientists and Engineers in every field. JoCI provides an outlet for Research findings and reviews in areas of Control & Instrumentation found to be relevant for National and International recent developments & research initiative. The aim and scope of the Journal is to provide an academic medium and an important reference for the advancement and dissemination of Research results that support high level learning, teaching and research in the domain of Control & Instrumentation. Finally, I express my sincere gratitude and thanks to our Editorial/ Reviewer board and Authors for their continued support and invaluable contributions and suggestions in the form of authoring writeups/ reviewing and providing constructive comments for the advancement of the journals. With regards to their due continuous support and co-operation, we have been able to publish quality Research/Reviews findings for our customers base. I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

Dr. Archana Mehrotra Director STM Journals

Journal of Control & Instrumentation

Contents

1. Multisensor Data Fusion based Intelligent Temperature Measurement Technique Santhosh K.V., Rachana Priyadarshini, Saloni

2. Comparison of Mamdani and Sugeno Fuzzy Inference Systems for a Three Tank Level Control System Vijaya Lakshmi K., Rao P. D. P., Srinivas P.

3. Designing of Low Pass Finite Impulse Response Filter using Radial Basis Function Neural Network Singh M., Thakare V. V.

4. Experimental Setup for the Measurement of Low Temperature Seebeck Coefficient of Single Crystal and Bulk Materials Naik I., Rastogi A. K.

Journal of Control & Instrumentation ISSN: 2229-6972 (online), ISSN: 2347-7237 (print) Volume 5, Issue 2 www.stmjournals.com

Multisensor Data Fusion based Intelligent Temperature Measurement Technique Santhosh K.V.*, Rachana Priyadarshini, Saloni Department of Instrumentation & Control Engineering, Manipal Institute of Technology, Manipal, India Abstract Design and validation of a temperature measurement technique using fusion of temperature sensor like resistance temperature detector (RTD), and thermistor is proposed in this work. The objective of proposed work is to design a technique using fuzzy logic algorithms to fuse two different sensors having dissimilar characteristics. A fuzzy logic system is trained to produce an output for a temperature measurement system which is (a) more linear input-output characteristics as compared to thermistor, (b) characteristics like offset and saturation present in output of RTD is reduced, and (c) detection and identification of fault if any in sensor with diagnostics. The proposed multi sensor system once trained is validated by applying it in real life application. Results produced by proposed system shows successful implementation of an intelligent temperature system.

Keywords: Temperature, fault detection, MSDF, fuzzy, LabVIEW

Journal of Control & Instrumentation ISSN: 2229-6972 (online), ISSN: 2347-7237 (print) Volume 5, Issue 2 www.stmjournals.com

Comparison of Mamdani and Sugeno Fuzzy Inference Systems for a Three Tank Level Control System Vijaya Lakshmi K.*, Rao P. D. P., Srinivas P. Department of EIE, VR Siddhartha Engineering College, Vijayawada, India Abstract The level control of a three tank system has become a research focus due to the nonlinear process and multivariables. It is well known that the conventional controllers are suitable to control linear processes and their design is based on the exact mathematical model. In this paper, we developed a mathematical model for a three tank system and proposed an effective controller design based on fuzzy logic by which more reliable and precise control can be achieved. We implemented P, PI, and PID controllers for three tank system using Mamdani and Sugeno fuzzy inference systems. Here, the auto tuning of proportional, integral, and derivative constants are performed using fuzzy controllers for optimum response. The results from these models for P, PI, and PID controllers are compared and observed that Sugeno FIS shows the superiority over mamdani in terms of rise time, settling time, and overshoot.

Keywords: Three tank system, modeling, fuzzy logic controller (flc), mamdani fis, sugeno fis

Journal of Control & Instrumentation ISSN: 2229-6972 (online), ISSN: 2347-7237 (print) Volume 5, Issue 2 www.stmjournals.com

Designing of Low Pass Finite Impulse Response Filter using Radial Basis Function Neural Network Singh M.*, Thakare V. V. Department of Electronics Engineering, Madhav Institute of Technology and Science, RGPV, Bhopal, Gwalior, Madhya Pradesh, India Abstract The present paper investigates an approach to design and analysis of a low pass finite impulse response (FIR) filter using artificial neural network. The main aim of design is to find out the filter coefficients that define the filter transfer functions. A datasheet of 40 different values of h (n), i.e., coefficient of digital low pass FIR filter are used for filter designing. In this paper Radial Basis Function method is used for train artificial neural network. A combination of digital signal processing algorithm and neural network is obtained with the help of MATLAB to produce effective algorithm for digital filter design is used in the present work.

Keywords: Artificial neural network (ANN), digital signal processing (DSP), finite impulse response (FIR)

Journal of Control & Instrumentation ISSN: 2229-6972 (online), ISSN: 2347-7237 (print) Volume 5, Issue 2 www.stmjournals.com

Experimental Setup for the Measurement of Low Temperature Seebeck Coefficient of Single Crystal and Bulk Materials Naik I.1*, Rastogi A. K.2 1

Department of Physics, North Orissa University, Baripada 757003, India School of Physical Sciences, Jawaharlal Nehru University, New Delhi 110067, India

Abstract A differential thermopower setup is fabricated for both the single crystal and bulk materials in the temperature range of 16–320 K. One advantage of this apparatus is that the sample separation can be changed according to the requirement between 2 and 5 mm. In this setup silver paint is used for the improvement of thermal and electrical conductivity between copper (thermocouple) leads and material. Seebeck coefficients are measured using a filter circuit at fixed temperature by making different temperature gradients for highly resistive compounds (<100 K) and continuously with a temperature difference of 0.3–0.5 K in case of metallic compounds. This setup is calibrated by using the high purity lead material and used it for the calculation of absolute seebeck coefficient of materials of interest. Our calculated Seebeck coefficient of copper from the measurement value of lead differs from the standard value of copper by +1.4 μV/K with a transition around 41 K related to the silver contain.

Keywords: Thermo power, differential method, experimental design, computer automation