Stochastic Modeling and Multi Regime GNC Optimization for the Stellaris RS-1 Reusable Launch Vehicle (RLV) via Nonlinear 6-DOF Dynamics and Integrated PID-MPC Architectures in MATLAB & Simulink
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Rocket takeoff and landing are among the most critical phases of a mission, requiring precise control under highly dynamic and nonlinear conditions. This study presents a comprehensive modeling and simulation framework for rocket ascent and descent using MATLAB and Simulink. A physics based mathematical model incorporating thrust, drag, gravity, and variable mass dynamics is developed to represent rocket motion. Advanced control strategies, including PID, Linear Quadratic Regulator (LQR), and Model Predictive Control (MPC), are implemented to regulate key flight parameters such as altitude, velocity, and attitude. The integrated Simulink model enables closed loop simulations of takeoff, gravity turn, and controlled landing, with performance evaluated under realistic disturbances. Results demonstrate stable trajectory tracking, smooth attitude transitions, and effective disturbance rejection. The study highlights the capability of modern control techniques in enhancing the reliability and precision of reusable rocket operations, providing valuable insights for the design and optimization of autonomous guidance and control systems.
