Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates. (arXiv:2207.06362v1 [math.OC])

We present the implementation of nonlinear control algorithms based on linear
and quadratic approximations of the objective from a functional viewpoint. We
present a gradient descent, a Gauss-Newton method, a Newton method,
differential dynamic programming approaches with linear quadratic or quadratic
approximations, various line-search strategies, and regularized variants of
these algorithms. We derive the computational complexities of all algorithms in
a differentiable programming framework and present sufficient optimality
conditions. We compare the algorithms on several benchmarks, such as autonomous
car …

arxiv iterative linear math optimization programming quadratic optimization