热启动扰动（WASP）约束动态规划的一种算法
An Algorithm to Warm Start Perturbed (WASP) Constrained Dynamic Programs
摘要：
滚动时域最优控制问题在每一时间步计算解，以使系统运行在接近最优的路径上，然而，在许多实际情况下，边界条件，如外部输入，约束方程或目标函数，从一个时间步到下一个时间步变化很小。在这种情况下，每次重新计算最优解对实时应用来说是一个很大的负担。本文提出了一种新的算法来近似求解扰动约束动态规划，显着改善的计算负担时，目标函数和约束是轻微的扰动。该方法的关键在于确定最优策略中一阶摄动的封闭形式表达式，并得到受摄动约束动态规划问题的Lagrange乘子。该信息可用于初始化任何算法（例如拉格朗日乘子方法或增广拉格朗日方法）以用最小计算资源求解扰动动态规划问题。
英文摘要：
Receding horizon optimal control problems compute the solution at each time step to operate the system on a near-optimal path. However, in many practical cases, the boundary conditions, such as external inputs, constraint equations, or the objective function, vary only marginally from one time step to the next. In this case, recomputing the optimal solution at each time represents a significant burden for real-time applications. This paper proposes a novel algorithm to approximately solve a perturbed constrained dynamic program that significantly improves the computational burden when the objective function and the constraints are perturbed slightly. The method hinges on determining closed-form expressions for first-order perturbations in the optimal strategy and the Lagrange multipliers of the perturbed constrained dynamic programming problem are obtained. This information can be used to initialize any algorithm (such as the method of Lagrange multipliers, or the augmented Lagrangian method) to solve the perturbed dynamic programming problem with minimal computational resources.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
