An adaptive multiple shooting strategy for optimal control

The use of multiple shooting has become the standard for the numerical solution of optimal control problems. We investigate how multiple shooting affects the convergence properties of Newton-type methods. For the first time, we conduct a systematic comparison of several multiple shooting strategies on a set of 40 optimal control problems. In addition, we consider … Read more

On regularized structure exploiting Quasi-Newton methods for inverse problems

This paper introduces a regularized, structure-exploiting Powell-Symmetric-Broyden (RSE-PSB) method under modified secant conditions for solving ill-posed inverse problems in both infinite dimensional and finite dimensional settings. The approximation of the symmetric, yet potentially indefinite, second-order term, which is neglected by standard Levenberg-Marquardt (LM) approaches, integrates regularization and structure exploitation directly within the Quasi-Newton (QN) framework, … Read more

Cubic Regularization Method based on Mixed Factorizations for Unconstrained Minimization

Newton’s method for unconstrained optimization, subject to proper regularization or special trust-region procedures, finds first-order stationary points with precision $\varepsilon$ employing, at most, $O(\varepsilon^{-3/2})$ functional and derivative evaluations. However, the computer work per iteration of the best-known implementations may need several factorizations per iteration or may use rather expensive matrix decompositions. In this paper, we … Read more

Inexact Newton-Type Optimization with Iterated Sensitivities

This paper presents and analyzes an Inexact Newton-type optimization method based on Iterated Sensitivities (INIS). A particular class of Nonlinear Programming (NLP) problems is considered, where a subset of the variables is defined by nonlinear equality constraints. The proposed algorithm considers an arbitrary approximation for the Jacobian of these constraints. Unlike other inexact Newton methods, … Read more

Lifted Collocation Integrators for Direct Optimal Control in ACADO Toolkit

This paper presents a class of efficient Newton-type algorithms for solving the nonlinear programs (NLPs) arising from applying a direct collocation approach to continuous time optimal control. The idea is based on an implicit lifting technique including a condensing and expansion step, such that the structure of each subproblem corresponds to that of the multiple … Read more

Backward Step Control for Global Newton-type Methods

We present and analyze a new damping approach called backward step control for the globalization of the convergence of Newton-type methods for the numerical solution of nonlinear root-finding problems. We provide and discuss reasonable assumptions that imply convergence of backward step control on the basis of generalized Newton paths in conjunction with a backward analysis … Read more

Cubic-regularization counterpart of a variable-norm trust-region method for unconstrained minimization

In a recent paper we introduced a trust-region method with variable norms for unconstrained minimization and we proved standard asymptotic convergence results. Here we will show that, with a simple modification with respect to the sufficient descent condition and replacing the trust-region approach with a suitable cubic regularization, the complexity of this method for finding … Read more