International Research Journal of Education and Technology

This investigation focuses on the application and effectiveness of Proportional-Integral-Derivative (PID) controllers integrated with sensor fusion for feeding filtered outputs to controllers of unmanned vehicles, including drones, autonomous ground vehicles, and underwater vehicles. Sensor fusion methods are widely used in control systems to enhance response time, reduce steady-state error, and improve overall system stability. This study leverages Simulink to simulate noisy sensor data and system dynamics, implementing sensor fusion algorithms to produce filtered state estimates. The entire control process, including PID control and sensor fusion, is simulated in MATLAB Simulink, where the primary outputs are the filtered state estimations and the resulting system responses. These outputs are critical in evaluating the effectiveness of PID control strategies and validating the noise reduction achieved through sensor fusion. Additionally, the study evaluates the limitations of PID controllers under dynamic and uncertain conditions, offering insights into potential enhancements for achieving optimal stability and robustness in real-time applications.

Key Words: Proportional-Integral-Derivative (PID), unmanned vehicles,. Sensor fusion, MATLAB Simulink, stability and robustness.