| Citation: | WU Jie, ZHANG Cheng, LI Miao, et al. Rocket return trajectory tracking guidance based on convex optimization and LQR[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(11): 2270-2280. doi: 10.13700/j.bh.1001-5965.2021.0084(in Chinese)
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For the powered descent phase of the reusable launch vehicle, various strict process constraints, terminal constraints and requirements on fuel saving exist, which bring great challenges to the guidance. This paper proposes a trajectory tracking guidance method based on convex optimization and linear quadratic regulator (LQR). The improved receding horizon convex optimization method is used to track the reference velocity of the rocket without requiring accurate thrust control input, which greatly simplifies the optimization model, and thus saves the computational cost of solving the optimal control problem. Meanwhile, the fuel is reduced as far as possible under various initial errors and model errors. On the other hand, the LQR technique is used to track the position of the rocket with high precision. The simulation results show that compared with the traditional LQR tracking guidance method, the proposed method can obtain comparable tracking accuracy, while greatly reducing fuel consumption. And compared to the existing receding horizon convex optimization, the proposed method can evidently reduce the computational cost and improve reliability.
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