With advancements in reusable liquid rocket engine technology to meet the diverse demands of space missions, engine systems have become increasingly complex. In most cases, these engines rely on stable open-loop control and closed-loop regulation systems. However, due to the high degree of coupling and nonlinear dynamics within the system, most transient adjustments still depend on open-loop control. Open-loop control often fails to provide the optimal control strategy when encountering external disturbances. To address this issue, we introduce the intrinsically motivated twin delayed deep deterministic (TD3) algorithm, specifically designed for the startup process of LOX/Kerosene high-pressure staged combustion engine. This approach leverages intrinsic motivation to enable the algorithm to adapt to the abrupt parameter changes during the start-up process. A series of comprehensive experiments were conducted to verify the effectiveness of our method. The experimental results demonstrate that our method outperforms both the PID method and previous researchers' reinforcement learning methods based on the TD3 algorithm and DDPG, achieving a faster and more stable start-up process and significantly enhancing engine performance.

This paper proposes a controller design for the electric pump of a deep-throttling rocket engine. The nonlinearity of the system is taken into consideration by analyzing the gap metric. Then, proportional-integral-derivative controller and gain-scheduling linear quadratic regulator are designed. Analyzing the amplitude- and phase-frequency characteristics as well as the pole-zero distribution of the system, the results show that the designed controllers can stabilize the linearized equations in incremental form at different operating points. This indicates that these two controllers are available for the original system in the whole range of working conditions and this is verified in the simulation. Meanwhile, the comparison between proportional-integral-derivative controller and gain-scheduling linear quadratic regulator is presented. It demonstrates that the proportional-integral-derivative controller is better at tracking both step and ramp signals but with worse control signals. It means that the proportional-integral-derivative controller seems less suitable for real use due to severe oscillations. Meanwhile, the parameter tuning of a proportional-integral-derivative controller depends on more extensive manual tuning. Therefore, the gain-scheduling linear quadratic regulator is preferred.