Conducted system-level sensitivity studies using Monte Carlo simulations to evaluate vehicle performance to meet mission objectives and help teams optimize their subsystems.
Developed MATLAB scripts to accelerate Monte Carlo data generation using Parallel Toolbox, along with post-processing scripts to assess vehicle/mission requirement violations, plotting routines for vehicle performance analysis, and GUIs for streamlined flight simulation data analysis.
Collaborated with cross-disciplinary teams to ensure accurate uncertainty implementation and subsystem modeling.
Presented Monte Carlo results to the board, providing strategic recommendations for autopilot algorithm tuning, improved mode transition conditions, and refinement of GNC requirements.
Developed physics based models and simplified complex simulations by using MATLAB’s Linear Analysis Toolbox and replacing physics-based models with accurate emulations.
Developed unit tests for vehicle models, code validation and model fidelity.
Ensured accurate interfacing between flight software, simulation models, and external hardware using ICDs.
Tuned autopilot gains and selected optimal controller architecture by leveraging linear analysis and Monte Carlo sensitivity studies
Utilized MATLAB Coder toolbox to generate C++ code for flight software
Exposed to advanced guidance algorithms, including proportional navigation and GENEX, autopilot tuning using linear analysis tools, modern control theory with Dynamic Inversion, and error estimation fusing onboard models and sensor feedback, structural coupling and ground vibration testing for structural filtering.
Engineering Student Researcher
Control Systems Laboratory, Dr. Shankar
Long Beach, California
05.2022 - Current
Developed a 6DOF that solved the EOM of quadcopter to simulate its dynamics in augmented reality using the Unity game engine(C# ), to support a psychology research team studying human response times and stress levels during flight.
Researched areas of vector calculus, aerodynamics principles, flight mechanics, and kinematics to ensure realistic flight characteristics .
Developed and Implemented virtual displays to help pilots interpret flight data, such as velocity, position, trajectory, and altitude.
Developed C# scripts to interface with external hardware, including a yoke and rudder pedals, to translate pilot inputs into augmented control commands.
Education
Bachelor of Science - Aerospace Engineering
California State University Long Beach
05.2023
Skills
Simulink
Matlab
C
Jira
Bitbucket
Source Tree
Jama
Beyond Compare
Personal Projects
Assembled a custom avionics stack with off-the-shelf electronics, including IMU (MPU 6050), Tenssy, Adafruit GPS, and Arduino SD card reader, to sense vehicle states and log autopilot inputs.
Utilized Onshape CAD software, XFLR CFD software, and custom test rigs to obtain mass properties, aerodynamic stability derivatives, and motor dynamics for accurate vehicle modeling in Simulink.
Developed physics-based Simulink models for 3D-printed drones and airplanes to identify optimal controllers (PID, PD, feedforward, and LQR) for Guidance and autopilot command tracking.
Created custom C++ math libraries for linear algebra and numerical methods, enhancing computation of vehicle dynamics.
Designed 2D guidance loops using proportional navigation in Simulink, integrating real-time vehicle tracking for position, velocity, and orientation using IMU feedback.
Implemented low-pass filters on sensor feedback to reduce MPU6050 noise.
Implemented Kalman Filter to fuse sensor feedback from GPS, Pilot tube and IMU navigation solution