基于MPC的带动力高超声速飞行器轨迹跟踪

Trajectory tracking of powered hypersonic vehicles based on MPC

针对带动力高超声速飞行器上升段制导问题,提出了一种基于凸优化的模型预测控制(MPC)轨迹跟踪方法。通过在模型预测控制优化模型中添加过程约束、控制量变化率罚函数项,提升带动力高超声速飞行器控制能力。对模型预测控制算法中的轨迹跟踪问题进行凸化和离散化,使用序列凸优化方法求解每个制导周期中的跟踪控制量;为加快序列凸优化的收敛速度,进一步提出基于轨迹误差的初值修改方法。仿真结果表明该方法具有较好的适应性,相比LQR方法可有效抑制控制量振荡和过饱和问题。

Aiming at solving trajectory tracking problems of powered hypersonic vehicles, a model predictive control(MPC) method using convex optimization is proposed. MPC can improve the control ability of powered hypersonic vehicles when adding path constraints and penalty terms of the controls’ changing rate to the open-loop optimization problem. The discretization and convexification of the trajectory tracking problem are conducted in every time step to transform it into a convex optimization problem, which could be solved by the sequential convex optimization method. To further enhance the convergence rate of the solving process, a technique to modify the initial value is proposed. Simulation results show that the proposed method performs better at suppressing the vibration of controls and handling constraints than an LQR controller, indicating its practicality to the trajectory tracking problem.