A quasi-Newton differential dynamic programming algorithm for discrete- time optimal control
We develop a quasi-Newton differential dynamic programming algorithm (QDDP) for discrete-time optimal control problems. In the spirit of dynamic programming, the quasi-Newton approximations are performed in a stagewise manner. We establish the global convergence of the method and also show a superlinear convergence rate. Among other advantages of the QDDP method, second derivatives need not be calculated. In theory, the computational effort of each recursion grows proportionally to the number of stages N, whereas with conventional quasi-Newton techniques which do not take advantage of the optimal control problem structure, the growth is as \(N^ 2\). Computational results are also reported.
quasi-Newton differential dynamic programming algorithm
scientific article; zbMATH DE number 4020940