Thrust vector control and state estimation architecture for low-cost small-scale launchers
Pedro dos Santos, Paulo Oliveira
TL;DR
The paper addresses stabilizing low-cost, solid-propellant small-scale launchers with thrust vectoring by integrating navigation and control. It develops a non-linear 6-DoF launcher model and uses a linearized, time-varying representation with gain scheduling, enabling an LQR with integral action (LQI) controller and complementary Kalman-based state estimation. The navigation stack combines IMU/GNSS sensing with Attitude and Position Complementary Filters and a Kalman filter for optimal state estimates, reducing computational load. Simulation results demonstrate robust attitude tracking under disturbances and model uncertainties, validating the architecture and highlighting the COM position as a key design parameter for performance.
Abstract
This paper proposes an integrated architecture for Thrust Vector Control (TVC) and state estimation for low-cost small-scale launchers, naturally unstable, and propelled by a solid motor. The architecture is based on a non-linear, six-degrees-of-freedom model for the generic thrust-vector-controlled launcher dynamics and kinematics, deduced and implemented in a realistic simulation environment. For estimation and control design purposes, a linearized version of the model is proposed. Single-nozzle TVC actuation is adopted, allowing for pitch and yaw control, with the control law being derived from the Linear Quadratic Regulator (LQR) with additional integral action (LQI). The control system is implemented through gain scheduling. Full state estimation is performed resorting to complementary kinematic filters, closely related to linear Kalman fitering theory. The architecture, composed by the navigation and control systems, is tested in simulation environment, demonstrating satisfactory attitude tracking performance and robustness to both external disturbances and model uncertainties.