Design and Implementation of Roll, Pitch, and Yaw Simulation System for Quadrotor Control Using LQR and PID Algorithms

Abstract

Abstract

The performance of a control system is often evaluated based on its ability to achieve minimal settling time and rise time. However, an optimal control system must also exhibit rapid and precise rotational responses to external commands, ensuring dynamic stability and responsiveness. This study focuses on the design and implementation of a DC motor speed control system using optimal control techniques to enhance settling time, rise time, and overall system performance. The research employs two prominent methods: the Proportional-Integral-Derivative (PID) controller and the Linear Quadratic Regulator (LQR) algorithm. Optimization in the LQR method is achieved by tuning the Q and R matrices to derive the optimal gain feedback (K) that minimizes the quadratic cost function. The process begins with mathematical modeling of the DC motor within the PID controller framework, enabling seamless integration into the LQR calculation. The simulation and implementation of the control system are conducted in MATLAB Simulink, allowing for comprehensive analysis of the system's dynamic responses. The results demonstrate the comparative advantages of each control method, highlighting the practical implications for applications requiring precise rotational speed control. This research contributes to advancements in control engineering by providing a systematic approach to optimizing DC motor performance, with potential applications in robotics, automation, and aerospace systems. Future work includes experimental validation and exploration of adaptive methods for further enhancement of control robustness.