Jitendra Singh

I obtained my Master's degree from National Institute of Technology Surat guided by Prof. S.N. Sharma. My Master's thesis focused on the field of control systems, titled “Mathematical Modelling & Control design for Inverted Pendulum”. I developed a practical setup and implemented an LQR control for balancing & Energy Based Collocated Partial Feedback Linearization Control for Swing Up.

After my Master's degree, I gained experience as Teaching Assistant at Indian Institute of Technology Jodhpur and National Institute of Technology Surat. After that, I was an Assistant Professor under TEQIP-III at UCET Bikaner. Furthermore, I have gained Research experience at the Indian Institute of Science Bangalore and Indian Institute of Technology Jodhpur.

I am most interested in Robotics, Control Systems, Dynamics, Optimisation, Linear Algebra, Computer Vision, and Machine Learning.

Technical Skills: ROS, GAZEBO, MATLAB, Embedded System, Digital Control Design, Digital Filter Design, Estimation, Python and Embedded C.

Two Wheel Self Balancing Robot: Design Linear & Non Linear Control techniques for Balancing & Trajectory Tracking

The self-balancing robot is essentially an inverted pendulum. In this project, I simulated non-linear mathematical models and implemented an LQR control in MATLAB to balance the robot at upward position. I then implemented a Feedback Linearization control for tracking the desired trajectory. Once I obtained stable simulation results, I implemented these control techniques on real hardware to validate simulation results.

 [PDF | Video | Simulation File]

Fuse IMU data using Complementary Filter
In this project, I Implemented Complementary Filter to Fuse Gyro & Accelerometer Data of IMU (MPU9250). I used Rosserial to send raw data from the IMU to ROS. I then created a GUI to test the performance of Filter using rqt_gui. Next, I published the output data of the filter on MATLAB for visualizing 3D Animation.

 [PDF | Video]

Mathematical modelling & controller design for INVERTED PENDULUM
The Primary objective of this project was to create a control system that could effectively balance a Inverted Pendulum using LQR control and swing up using Energy Based Swing up control. This project covered the full scope of design including creating a valid model of the system,... identifying numerical values for the model parameters, assembling the system hardware, and implementing the control system using MATLAB Simulink support package for Arduino Mega (8-bit AVR Microcontroller) to interface with the DC motor. I used a linear guide actuator system that is taken out from defective Inkjet Printer for develop a linear actuator and some other parts have been designed using 3D printer to manipulate the whole model into this setup. I implemented an Energy based Collocated Partial Feedback Linearization control for swing up & LQR control for balance it at the top. finally, I have done this in Control system lab at IIT Jodhpur. Read more

 [PDF | Video]

Inverted Pendulum: design Swing up & LQR Control using MATLAB Code

I implemented Energy based collocated partial feedback linearization control for Swing Up the Pendulum and LQR for balancing at upward position in MATLAB code.

 [PDF | Video | MATLAB Code]

Inverted Pendulum: design Swing up & LQR Control using MATLAB Simulink

I implemented Energy based collocated partial feedback linearization control for Swing Up the Pendulum and LQR for balancing at upward position in MATLAB Simulink.

 [PDF | Video | Simulation File]

An interactive Matlab GUI to tune PID gains for a line following robot

The software I developed was a graphical user interface (GUI) that is for monitoring the response of robot and tuning the PID's gains in real-time. I used the conventional trial-and-error method for tuning the PID's gains for Line Following Robot.

 [Video]

Model Based Control Design for Speed Control of DC Motor using MATLAB & Simulink

A Model-Based Control design was used in this project. I first experimented on the DC motor by giving step input voltage to it and recording the output speed. Next, I estimated the first-order transfer function of the motor by using the SISO tool in MATLAB. Then, I used Control System Toolbox to design a PID controller. Lastly, using Automatic Code Generating in Simulink for all Arduino code, including control, sensor, and serial communication.

 [Video]

A new approach for line following robot using radius of path curvature and differential drive kinematics

Jitendra Singh, Prashant Singh

6th IEEE International Conference CERA, 2017

 [PDF | Video]