Description
Development of control strategies for altitude and attitude control of Unmanned Autonomous Vehicle May 2017 - August 2017 Developed Nonlinear Mathematical Model for Quadrotor States * Utilized MATLAB and Simulink to find the equilibrium point and linearize a Quad Rotor system around the equilibrium point with the help of 'Gradient Descent Algorithm' * Developed Least squares batch processing algorithm using python libraries such as NumPy Pandas * Implemented 'Extended Kalman Filter' for Estimating Quadrotor system states from IMU sensor Data * Designed Control mechanism for attitude and altitude control of the Quad Rotor system using state feedback design with integral error gain and Linear Quadratic Regulator * Implemented Object Detection Algorithms via Deep-Learning for Obstacle avoidance in Python using Open CV SSD Tensor Flow Integrated Vicon Camera System to the Quadrotor for Motion Capture * Control of Self Driving Robotic Car using Extended Kalman Filter and LQR August 2017 - March 2018 * Utilized MATLAB and Simulink to find the equilibrium point and linearize Robotic system around the equilibrium point with the help of 'Steepest Descent Algorithm' * Designed and Implemented Extended Kalman Filter for Lateral and Longitudinal Velocities of the System using sensor data such as IMU (Inertial Measurement Unit) * Applied LQR technique for State Feed Back Control * Nonlinear Adaptive Control of Quadrotor UAVs using Adaptive Back Stepping Technique January 2017 - April 2017 * Designed 'Adaptive Back Stepping Control Algorithm' using Lyapunov Stability for Quad Rotor system * Implemented 'Extended Kalman Filter' for Estimating Quadrotor system states using data from Vicon Camera * Calibrated to reduce the impact of wing loss/damage to certain extent when Quad Rotor is in flight * Verified developed non-linear control algorithm on a Quadrotor in a restricted environment
Education
SCHOOL | MAJOR | YEAR | DEGREE |
---|---|---|---|
Wright State University | Electrical Engineering | 2018 | Master Degree |