SIJJIL KHAN

SIJJIL KHAN

Class of 2024
BS Computer Engineering

Aspiration Statement

Passionate about leveraging technology for social impact.

Core Skills

  • Agile Project Management
  • C/C++
  • Cypher
  • Design Thinking
  • Gazebo
  • Leadership
  • MATLAB
  • Python
  • Simulink
  • SQL
  • Verilog

Academic Awards / Achievements

  • HU TOPS Scholar

Experience

Leadership / Meta-curricular

  • Stanford University Summer International Honors Program 2023
  • President of Entrepreneurship Club
  • Futsal Lead (Sports and Recreational Society) and Girls Futsal Team Captain (2022-2024)
  • Orientation Leader NSO 2022

Final Year Project

Project Title

Enhancing Precision and Accuracy: PD vs. Sliding Mode Control with Chattering Suppression in Quadrotor Drones

Description

In this study, we first study the kinematics and dynamics of quadrotor drones, focusing on achieving precise control and trajectory adherence in aerial robotics. We compare two control approaches: proportional-derivative (PD) control and sliding mode control (SMC). To enhance accuracy and reduce chattering, our study explores different sliding surface equations within SMC, including the soft sign and other squashing functions. Our control methodology involved two loops: the primary loop for controlling location and the secondary loop for controlling orientation. By incrementally increasing the drone's altitude while minimizing chattering, we demonstrated the efficiency of these control techniques, allowing the drone to navigate in a spiral pattern with improved stability and precision. This research contributes to a deeper understanding of quadrotor drone dynamics and informs effective control strategies for aerial robotics applications.