[图书][B] Variational analysis and applications
BS Mordukhovich - 2018 - Springer
Boris S. Mordukhovich Page 1 Springer Monographs in Mathematics Boris S. Mordukhovich
Variational Analysis and Applications Page 2 Springer Monographs in Mathematics Editors-in-Chief …
Variational Analysis and Applications Page 2 Springer Monographs in Mathematics Editors-in-Chief …
Solving mathematical programs with complementarity constraints arising in nonsmooth optimal control
This paper examines solution methods for mathematical programs with complementarity
constraints (MPCC) obtained from the time-discretization of optimal control problems (OCPs) …
constraints (MPCC) obtained from the time-discretization of optimal control problems (OCPs) …
Online feedback equilibrium seeking
G Belgioioso, D Liao-McPherson… - … on Automatic Control, 2024 - ieeexplore.ieee.org
This paper proposes a unifying design framework for dynamic feedback controllers that track
solution trajectories of time-varying generalized equations, such as local minimizers of …
solution trajectories of time-varying generalized equations, such as local minimizers of …
A novel micromechanics-enhanced phase-field model for frictional damage and fracture of quasi-brittle geomaterials
Cracking in quasi-brittle geomaterials is a complex mechanical phenomenon, driven by
various dissipation mechanisms across multiple length scales. While some recent promising …
various dissipation mechanisms across multiple length scales. While some recent promising …
Time-distributed optimization for real-time model predictive control: Stability, robustness, and constraint satisfaction
Time-distributed optimization is an implementation strategy that can significantly reduce the
computational burden of model predictive control. When using this strategy, optimization …
computational burden of model predictive control. When using this strategy, optimization …
The Levenberg–Marquardt method: an overview of modern convergence theories and more
A Fischer, AF Izmailov, MV Solodov - Computational Optimization and …, 2024 - Springer
Abstract The Levenberg–Marquardt method is a fundamental regularization technique for
the Newton method applied to nonlinear equations, possibly constrained, and possibly with …
the Newton method applied to nonlinear equations, possibly constrained, and possibly with …
A unified analysis of descent sequences in weakly convex optimization, including convergence rates for bundle methods
We present a framework for analyzing convergence and local rates of convergence of a
class of descent algorithms, assuming the objective function is weakly convex. The …
class of descent algorithms, assuming the objective function is weakly convex. The …
Nonlinear model predictive control of a diesel engine air path: A comparison of constraint handling and computational strategies
M Huang, H Nakada, K Butts, I Kolmanovsky - IFAC-PapersOnLine, 2015 - Elsevier
This paper presents the development of a Nonlinear Model Predictive Controller (NMPC) for
the diesel engine air path. The objective is to regulate the intake manifold pressure (MAP) …
the diesel engine air path. The objective is to regulate the intake manifold pressure (MAP) …
A globally convergent proximal Newton-type method in nonsmooth convex optimization
The paper proposes and justifies a new algorithm of the proximal Newton type to solve a
broad class of nonsmooth composite convex optimization problems without strong convexity …
broad class of nonsmooth composite convex optimization problems without strong convexity …
A Bregman forward-backward linesearch algorithm for nonconvex composite optimization: superlinear convergence to nonisolated local minima
We introduce Bella, a locally superlinearly convergent Bregman forward-backward splitting
method for minimizing the sum of two nonconvex functions, one of which satisfies a relative …
method for minimizing the sum of two nonconvex functions, one of which satisfies a relative …