论文部分内容阅读
针对火星进入段控制受约束、大气环境以及探测器自身参数不确定性等问题,提出控制受约束的火星最优鲁棒进入制导方法.将针对参数不确定系统的最优性能指标转换为针对标称系统的修正性能指标;同时考虑控制约束,在性能指标中引入饱和函数,将制导问题转化为求解修正Hamilton-Jacobi-Bellman(HJB)方程问题;由于HJB方程是偏微分方程,求解有难度,利用神经网络的逼近能力近似求解.本文制导方法保证了不确定系统有最优的性能指标上界和较强的鲁棒性.最后将其应用到火星进入制导中,仿真结果表明系统存在不确定的情况下,仍可以很好地满足火星进入段终端条件,控制量也在约束的范围内,从而验证所提方法的有效性.
In view of the constraint of Mars entering section control, the atmospheric environment and the uncertain parameters of the detector itself, the optimal constrained Mars approach to robust guidance is proposed. The optimal performance index for the uncertain system of parameters is transformed into the target We consider the control constraints and introduce the saturation function into the performance index to convert the guidance problem into solving the Hamilton-Jacobi-Bellman (HJB) equation. Because the HJB equation is a partial differential equation, it is difficult to solve the problem. The approximation ability is approximated by using the neural network approximation ability.The guidance method in this paper guarantees the upper bound and the robustness of the optimal performance of the uncertain system.Finally it is applied to the Mars entry guidance and the simulation results show that the system has uncertainties , We can still meet the requirements of Mars entering the terminal well and the control volume is within the bounds of the constraints, so as to verify the effectiveness of the proposed method.