Control Project
Resume:
PREETHI R
:**********@*****.***
To seek a challenging career in technical and research and to excel in my field through hard work, research, skills and perseverance. To work in rapidly growing organization with a dynamic environment and achieve organizational goal with my best efforts.
Course
Discipline/ Specialization
School/College
Board/ University
Year of Passing
Percentage
M.Tech
Control and Automation
VIT, Vellore
VIT University
2015
8.88CGPA
B.E
Electronics and Communication
E.W.I.T, Bangalore
V.T.U
2012
69.12
P.U.C
P.C.M.C
MLACW PU College,
Bangalore
P.U
2008
69.17
S. S. L.C
S.S.L.C
SCVKHS,
Bangalore
K.S.E.E
2006
91.36
Languages: C, Verilog, VHDL
Software tools: Keil, MATLAB, CC Studio, Keyence PLC, NI lab view
Operating systems: WINDOWS 2000/07/08/XP, DOS 6.0
Area of interest: Control systems, Process automation, Industrial automation, Logic Design, Communication protocols
PG project: Project work carried out at Control Dynamics and Simulation group, ISRO Satellite Centre, Bangalore.
Title: Design of lunar soft landing guidance with terminal control constraints
Duration: 7months (Oct 2014 to May 2015)
Description:
This thesis work is aimed at developing analytical and optimal/non-optimal guidance algorithms for the powered descent phase of lunar soft landing mission. The algorithms are able to meet mission requirements in terms of desired position, velocity and orientation at final time during phases of powered descent such as rough braking, fine braking and vertical descent. The algorithms proposed to be developed, have the capability to be implemented in real flight thus giving closed loop results at every sampling instants which henceforth will be mentioned as guidance cycle. This thesis work is credited with novel developments on an optimal guidance algorithm and a non-optimal polynomial guidance law. An existing Constrained Terminal Velocity Guidance (CTVG) was augmented to meet final orientation constraints. The Polynomial Guidance law was augmented for fuel optimality.
Title: Artificial neural network based inverse model control of a nonlinear process
Duration: 4months
Description:
In process industries the control of a non linear process is a complicated task. One such example of a non linear process is controlling the liquid level in the conical tank. Artificial Neural Network (ANN) based Direct Inverse Control (DIC) is developed to control the non linear dynamics of conical tank. ANN is trained by back propagation algorithm. The direct inverse control realizes a good dynamic behaviour of interacting and non interacting conical tank system
Title: PSO Tuned Wavelet Neural Network for Time Series Prediction
Duration: 4months
Description:
Developing neural network models for forecasting a sequence of events has been a challenging task in many domains, like, weather, finance, predictive control, etc. Wavelets neural network (WNN) has better approximation ability and error tolerance performance. It sufficiently utilizes the localization characteristics of wavelets combined with self-study and self-organizing functions of a common neural network. A simple and definite training algorithm for tuning WNN parameters using Particle Swarm Optimization (PSO) is used. The mean square error between network output and target was used as fitness function for PSO. In process modeling PSO tuned WNN model has high degree of closeness to the real time response.
UG Project: Project work carried out at Bharath Electronics Limited, Bangalore
Title: Development of analysis software for identifying the signal type in a .wav file
Duration: 4 months
Description:
In signal intelligence application, the security agencies need to continuously monitor communication sessions to detect unauthorized or illegal activities. This requires monitoring and filtering of unwanted data from a pool of vast data base. Manually, this task is impossible to carry out. Hence, automatic software needs to be developed so that the classification of different signal types can be carried out effectively. Once the signal is classified, it is forwarded for further processing. In an organization the signals received are stored in .wave format. A wave file format can store audio and non audio data bit streams. The received wave files can be voice, or data files. Since these files are in their raw format it is not possible to identify them. Hence software is required to identify and classify the files. It finds its application in signal intelligence and communication surveillance.
1.Ramkiran B, Preethi R, Rijesh M P, Bharat Kumar G V P, Philip N K, and Natarajan P, “Analytical Optimal Guidance Algorithm for Lunar Soft Landing with Terminal Control Constraints”, submitted to (under review) Second Indian Control Conference, 4-6 January 2016, Hyderabad, India.
2.R J Rajesh, Preethi R, Jaganatha Pandian B, Parth Mehata, “Artificial Neural Network based inverse model control of a Nonlinear Process”, accepted for presentation in IEEE International Conference on Computer, Communication and Control (ICCCC'15), 10-12 September 2015, Indore, India
3.Preethi R, Haripriya N, Vishvaa A, B Jaganatha Pandian (2014): “PSO Tuned Wavelet Neural Network for Time Series Prediction”, International Journal of Applied Engineering Research, Vol. 9, No. 22, pp. 123**-*****,
GATE 2015 and 2013 qualified.
Participated in Two days workshop on “Industrial Applications of Advanced Control & Estimation” Automatic Control and Dynamic Optimization Society, IISc, Bangalore.
Co-ordinated “National conference on advances in electronics and intelligent computing” at East West Institute of Technology, Bangalore.
Participated in Workshop on “Building and flying Micro air vehicles” at REVA College of Engineering, Bangalore.
Junior Certificate: Karnataka Music Vocal (KSEEB)
Name : PREETHI .R
Date of birth : 1st June 1991
Nationality : Indian
Languages known : Tamil, Kannada, Malayalam, English
Leisure Interests : Singing, Yoga, Badminton, Gardening
Declaration:
I hereby declare that the above information furnished by me is true and correct to the best of my knowledge.
Place: Bangalore Yours sincerely
Date: (PREETHI R)
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