Reusable Launch Vehicle Landing Online Guidance and Control Based on ESO-MPC and Convex Optimization

This paper proposes an integrated guidance and control framework for reusable launch vehicles to achieve pinpoint landing accuracy with optimal fuel consumption. Firstly, an offline trajectory planning method is developed by combining Gauss pseudospectral method and sequential convex optimization techniques. Then, for real-time implementation, a model predictive controller with disturbance compensation is designed to estimate and feed forward compensates disturbances in real time through an extended state observer. Unlike traditional trajectory tracking approaches, the proposed online guidance and control framework simultaneously optimizes trajectory planning and control execution, enabling robust performance under dynamic and uncertain conditions. Simulation results demonstrate that the method significantly improves landing precision while minimizing fuel consumption, validating its potential for reusable launch vehicles in precision landing missions.