We consider trajectory optimal control problems in which parameter uncertainty limits the applicability of control trajectories computed prior to travel. Hence, efficient trajectory adjustment is needed to ensure successful travel. However, it is often prohibitive or impossible to recalculate the optimal control in-transit due to strict time constraints or limited onboard computing resources. Thus, we propose a framework for quick and accurate trajectory approximations by using post-optimality sensitivity information. This allows the reduction of uncertain parameter space and an instantaneous approximation of the new optimal controller while using sensitivity data computed and stored pretransit.

翻译：本文研究轨迹最优控制问题，其中参数不确定性限制了预先计算的控制轨迹在实际应用中的有效性。因此，需要高效的轨迹调整机制来确保任务的成功执行。然而，由于严格的时间限制或机载计算资源有限，在任务过程中重新计算最优控制往往不可行甚至无法实现。为此，我们提出一种基于最优后灵敏度信息的快速精确轨迹近似框架。该方法通过利用预先计算并存储的灵敏度数据，能够有效缩减不确定参数空间，并实现对新型最优控制器的瞬时近似。