A parallel quadratic programming method for dynamic optimization problems
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Publication:499159
DOI10.1007/s12532-015-0081-7zbMath1321.90094OpenAlexW1971930153MaRDI QIDQ499159
Janick V. Frasch, Moritz Diehl, Sebastian Sager
Publication date: 30 September 2015
Published in: Mathematical Programming Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s12532-015-0081-7
quadratic programmingparallel algorithmsmodel predictive controldual decompositionstructure exploitation
Numerical methods involving duality (49M29) Quadratic programming (90C20) Newton-type methods (49M15)
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\texttt{acados} -- a modular open-source framework for fast embedded optimal control ⋮ Recent advances in quadratic programming algorithms for nonlinear model predictive control ⋮ FBstab: a proximally stabilized semismooth algorithm for convex quadratic programming ⋮ ALADIN‐—An open‐source MATLAB toolbox for distributed non‐convex optimization ⋮ A combined first‐ and second‐order approach for model predictive control ⋮ Inexact Newton-Type Optimization with Iterated Sensitivities ⋮ Lifted collocation integrators for direct optimal control in ACADO toolkit ⋮ A Sparsity Preserving Convexification Procedure for Indefinite Quadratic Programs Arising in Direct Optimal Control ⋮ Numerical Structure of the Hessian of the Lagrange Dual Function for a Class of Convex Problems ⋮ Multi-level iterations for economic nonlinear model predictive control ⋮ Distributed optimization and control with ALADIN ⋮ Solving nearly-separable quadratic optimization problems as nonsmooth equations ⋮ A parallel Newton-type method for nonlinear model predictive control ⋮ Newton projection with proportioning using iterative linear algebra for model predictive control with long prediction horizon ⋮ Multiple Shooting in a Microsecond ⋮ From linear to nonlinear MPC: bridging the gap via the real-time iteration ⋮ An Augmented Lagrangian Based Algorithm for Distributed NonConvex Optimization ⋮ qpDUNES ⋮ ParNMPC – a parallel optimisation toolkit for real-time nonlinear model predictive control
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- A numerically stable dual method for solving strictly convex quadratic programs
- qpOASES: a parametric active-set algorithm for~quadratic programming
- An auto-generated real-time iteration algorithm for nonlinear MPC in the microsecond range
- A tolerant algorithm for linearly constrained optimization calculations
- A nonsmooth Newton's method for discretized optimal control problems with state and control constraints
- Introductory lectures on convex optimization. A basic course.
- An effective implementation of the Lin-Kernighan traveling salesman heuristic
- Application of interior-point methods to model predictive control
- A nonsmooth version of Newton's method
- New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds
- Block-structured quadratic programming for the direct multiple shooting method for optimal control
- Partitioned Dynamic Programming for Optimal Control
- On the Implementation of a Primal-Dual Interior Point Method
- Numerically stable methods for quadratic programming
- A New Algorithm for Solving Strictly Convex Quadratic Programs
- An online active set strategy to overcome the limitations of explicit MPC
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