Venkatraman Renganathan - CV
Contact
Information
7825, McCallum Blvd,
Apt # 213, Dallas,
Texas, USA 75252
+1 480-628-9124
[email protected]
personal website
Education
University of Texas at Dallas (UTD) - Richardson, Texas - USA,
PhD, Mechanical Engg. - Control Systems, CGPA - 4.0/4.0, Expected: Dec 2019
• Thesis Topic: Design of Resilient Control for Large Scale Dynamical Networks
• Advisor: Dr. Tyler H. Summers
Arizona State University (ASU) - Tempe, Arizona - USA,
M.S., Electrical Engg. - Control Systems, CGPA - 3.76/4.0, Graduated: July 2016
• Thesis Topic: Kill Zone Analysis for a Bank-to-Turn EMRAAT Missile-Target
Engagement
• Advisor: Dr. Armando A Rodriguez
Anna University - Government College of Technology, Coimbatore, INDIA
B.E., Electrical & Electronics Engg., CGPA - 9.12/10.0, Graduated: May 2011
• Thesis Topic: Implementation of PLC for Relay Logic Controlled Electro-Hydraulic
Tube Bending Machine
• Advisor: Dr. V. Prasanna Moorthy
Research
Interests
Game Theory, Stochastic Controls, Distributed Control Algorithms, Machine Learning,
Resilient Control Design, Optimal Control.
Courseworks
Dynamics of Complex Networks & Systems, Nonlinear Systems, Robust Control Systems,
Optimal Control & Dynamic Programming, Real Analysis, Game Theory I (Coursera),
Game Theory II (Coursera), Linear Systems Theory, Feedback Systems, Random Signal
Theory, Optimal Control, Introduction To System Identification, Computer Controlled
Systems, Design of Multi-variable Control, Optimization, Machine Learning(Coursera),
Logic & Distributed Control Systems, Modern Control Theory, Numerical Methods,
Industrial Drives & Controls, Virtual Instrumentation, Digital Signal Processing.
Research
Experience
Dept. of Mechanical Engg., UTD, Richardson - USA August 2016 to present
Advisor: Dr. Tyler H. Summers
Topic: Resilient Control Design for mitigating attacks on Cyber-Physical systems using
Game Theory
Outline: Involves designing control strategies aiming for resilience on networked &
distributed robotics networks that are prone to cyber attacks and testing them on a
multi-robot testbed..
Dept. of Electrical Engg., ASU, Tempe - USA
January 2014 to July 2016
Advisor: Dr. Armando A Rodriguez
Topic: Kill Zone Analysis for a Bank-to-Turn EMRAAT Missile-Target Engagement
Outline: Involves building a MATLAB application for learning missile guidance control
systems. 6 DOF EMRAAT [Extended Medium Range Air-Air Technology] missile is
mathematically modeled along with 3DOF simple target aircraft having maneuvering
intelligence. The differential equations governing missile dynamics are solved using
different numerical integration techniques like Runge-Kutta methods to ensure that
the final miss distance is minimized. Missile Guidance is implemented using one of
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the following three algorithms namely Proportional navigation, Optimal Control and
Differential Game Theory. Similarly Target Maneuver is carried out using one of the
three techniques namely Constant Velocity, Riggs Vergaz Turn-Dive and Sheldon TurnClimb. Aerodynamic coefficients are calculated from look-up table obtained through
wind tunnel testing. Both missile plant with fin actuator dynamics and the nonlinear
gain scheduled autopilot are linearized around trim flight conditions and control design
using H∞ controller is carried out and various closed loop maps are analyzed to study its
robustness. MATLAB 3D Animation using VRML toolbox is carried out to visualize the
entire missile-target engagement. Also to increase the speed of operation, the Stability
Derivatives of the missile are studied for their complex dependency on parameters and
their respective mathematical models are proposed using curve-fitting techniques. Post
flight data analysis is carried out to study the effect of various design parameters upon
the miss distance which gave rise to an interesting resource allocation problem. The Kill
Zone of missile, where it can successfully intercept the target is estimated using binary
search algorithm. The obtained Kill Zone estimate is analyzed by varying various missile
parameters. With these results, missiles can be intelligently launched with high success
rate. This research can be extended to study an even more complicated problem, which
involves intercepting multiple target at the same time using missile resources, depending
upon the need of the hour and lethality of the target.
Teaching
Experience
Department of Mathematics & Statistics - ASU, Tempe - USA
Grader
September 2013 - June
MAT 265 - Calculus for Engineers - I
Fall
MAT 267 - Calculus for Engineers - III
Spring
MAT 265 - Elementary Linear Algebra
Summer
MAT 210 - Brief Calculus
Fall
MAT 265 - Calculus for Engineers - I
Spring
MAT 265 - Calculus for Engineers - I
Spring
MAT 211 - Math for Business Analysis
Spring
MAT 210 - Brief Calculus
Spring
2016
2013
2014
2014
2014
2015
2016
2016
2016
Instructional Aide
MAT 265 - Calculus for Engineers - I
MAT 170 - Pre-Calculus
MAT 142 - College Mathematics
MAT 170 - Pre-Calculus
MAT 142 - College Mathematics
2014
2014
2015
2015
2016
Summer
Summer
Summer
Fall
Summer
School of Mechanical, Aerospace, Chemical & Materials Engineering. - ASU
Grader
August 2014 - May 2015
CHE 461 - Process Dynamics and Controls
Fall 2014
CHE 494/598 - Introduction to System Identification
Spring 2015
Instructor: Dr. Daniel E Rivera, Ph.D
Control Systems Engineering Laboratory
ASU, Tempe - USA
Projects
Formation Control of Robots using Stochastic Control Approach
Formation Control of network of robots is an interesting problem which when efficiently
solved will be beneficial in improving the efficiency of services provided by network
of mobile agent systems such as distributed sensor networks and cooperative robot
surveillance. Formation Control is primarily used to design ad-hoc vehicular networks.
For example, cars can collectively sense information about traffic congestion and relay
them to other cars, toll stations, or centralized control junctions to facilitate traffic re-
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routing. Several other applications can become feasible if vehicles cooperate among
themselves to achieve a common goal. In this project report, a formation control
problem is formulated in a linear quadratic stochastic framework assuming that all the
agents are playing together as a team minimizing a common objective while tracking a
sinusoidal trajectory. Demonstration of open loop policy generation, obtaining closed
loop policy using dynamic programming and design of Model Predictive Controller are
shown in the simulations presented.
Prett-Garcia PID Controller with Control Relevant Identification
Using the PID controller tuning rules specified by Prett-Garcia design, the continuous
time Bed Calciner plant transfer function is discretized and control relevant identification
technique is applied using Iterative pre-filtering algorithm. The multiplicative error due
to estimation is maintained as low as possible throughout the bandwidth of interest.
Both modeling and controlling phases are integrated into a single process, thus, making
closed loop identification to give better results, even in the presence of hiccups in open
loop identification.
Optimal Control Algorithm for F-4 Aircraft to Climb in minimum time
The atmospheric data and non-linear flight data are modeled using linearization technique.
Keeping the thrust of flight at maximum value throughout the operation and the angle
of attack as manipulated variable, optimal control algorithm is executed to make the
modeled flight to reach height of 20 km in minimum time.
Optimal Control design for Semiconductor Furnace Temperature Control
System using Steepest Descent Approach
The overall furnace temperature has to be maintained constant at all time. Any ramp
up or ramp down operation has to take place without affecting overall temperature of
furnace. The steepest descent algorithm takes care of achieving the desired temperature
transition in minimum time. While the conjugate gradient method involves more
computational effort, the solutions converge very quickly.
Implementation of PLC for Relay Logic Controlled Electro-Hydraulic Tube
Bending machine
The tube bending machine selected from BHEL - Trichy, was over 3 decades, working
with relay logic control. The task was to revive it with cutting edge technology and
make the machine meet its current demand. The main constraint was the wear and
tear of the machine which it had acquired over 3 decades of working. Though new
techniques like CNC were available, a middle level PLC technology was proposed to
ensure an economical and optimal design, keeping in mind the constraints posed by the
machine. The machine was studied on a 360 degree basis with all kind of inputs from
engineers and workers working on it. Considering the number of input/output terminals
of the machine and futuristic implementations, S7 200 - Siemens PLC was chosen for
design purpose. Then an optimal PLC design with work flow diagrams, ladder logics and
simulations were proposed to the Chief Engineer of the plant. The proposed economical
design would increase the productivity of machine from bending 14 tubes per hour to
18 tubes per hour.
Project Guide: Dr. V. Prasanna Moorthy,
Email: [email protected]
Dept. of Electrical and Electronics Engineering,
Ph: +91 9443750031
Anna University - Coimbatore, INDIA.
Professional
Experience
Aspire Systems - India Pvt. Ltd., Chennai - INDIA
June 2011 to Sept 2012
Role: Software Engineer
Worked in Dotnet platform supported with SQL 2008 Server background. Got trained
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in developing windows and web applications using VB.NET and C#.NET. Performed
maintenance of training course enrollment web application for chemical industry client.
Developed a windows application for writing data sheets for chemicals, which reduced
the time to prepare one data sheet from 7 days to 4 hours.
References:
Project Manager: Kamal Chandramohan
[email protected]
HR Manager: Dinesh Kumaran
[email protected]
Aspire Systems - India Pvt. Ltd.,
Chennai - INDIA.
Awards
Student Award - Govt. College of Technology, Coimbatore - Anna University, INDIA
• GCT Alumni Association Scholarship for Academic Excellency
Fall 2009
References
Dr. Tyler H. Summers - PhD Advisor
Email: [email protected]
Assistant Professor in Mechanical Engineering,
Ph: +1 505-463-3121
University of Texas at Dallas, Richardson, Texas - USA
Dr. Armando A. Rodriguez - MS Thesis Advisor
Professor in Electrical Engineering,
Ira A. Fulton School of Engineering,
Arizona State University, Tempe - USA
Dr. Daniel E. Rivera
Professor in Chemical Engineering,
Ira A. Fulton School of Engineering,
Arizona State University, Tempe - USA
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Email: [email protected]
Ph: +1 480-332-1473
Email: [email protected]
Ph: +1 480-250-7063