Recent advances in quadratic programming algorithms for nonlinear model predictive control
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Publication:1633780
DOI10.1007/s10013-018-0311-1zbMath1416.90030OpenAlexW2893725532MaRDI QIDQ1633780
Moritz Diehl, Gianluca Frison, Dimitris Kouzoupis, Andrea Zanelli
Publication date: 20 December 2018
Published in: Vietnam Journal of Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10013-018-0311-1
Quadratic programming (90C20) Newton-type methods (49M15) Existence theories for optimal control problems involving partial differential equations (49J20)
Related Items (4)
An efficient bounded-variable nonlinear least-squares algorithm for embedded MPC ⋮ IPRQP: a primal-dual interior-point relaxation algorithm for convex quadratic programming ⋮ Zero-order optimization for Gaussian process-based model predictive control ⋮ Multi-level iterations for economic nonlinear model predictive control
Uses Software
Cites Work
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- blockSQP
- CVXGEN: a code generator for embedded convex optimization
- An alternative use of the Riccati recursion for efficient optimization
- qpOASES: a parametric active-set algorithm for~quadratic programming
- A parallel quadratic programming method for dynamic optimization problems
- An auto-generated real-time iteration algorithm for nonlinear MPC in the microsecond range
- A global piecewise smooth Newton method for fast large-scale model predictive control
- QPSchur: A dual, active-set, Schur-complement method for large-scale and structured convex quadratic programming
- The advanced-step NMPC controller: Optimality, stability and robustness
- Introductory lectures on convex optimization. A basic course.
- A continuation/GMRES method for fast computation of nonlinear receding horizon control
- An SR1/BFGS SQP algorithm for nonconvex nonlinear programs with block-diagonal Hessian matrix
- Application of interior-point methods to model predictive control
- Controlling the level of sparsity in MPC
- Model predictive control: recent developments and future promise
- Multiple Shooting in a Microsecond
- An Augmented Lagrangian Based Algorithm for Distributed NonConvex Optimization
- Projection-free parallel quadratic programming for linear model predictive control
- A Parametric Nonconvex Decomposition Algorithm for Real-Time and Distributed NMPC
- An Accelerated Dual Gradient-Projection Algorithm for Embedded Linear Model Predictive Control
- ACADO toolkit-An open-source framework for automatic control and dynamic optimization
- Time-optimal control of automobile test drives with gear shifts
- Two-Metric Projection Methods for Constrained Optimization
- A New Unblocking Technique to Warmstart Interior Point Methods Based on Sensitivity Analysis
- Efficient Numerical Methods for Nonlinear MPC and Moving Horizon Estimation
- Partitioned Dynamic Programming for Optimal Control
- BLASFEO
- A dual Newton strategy for scenario decomposition in robust multistage MPC
- Projected Newton Methods for Optimization Problems with Simple Constraints
- FORCES NLP: an efficient implementation of interior-point methods for multistage nonlinear nonconvex programs
- From linear to nonlinear MPC: bridging the gap via the real-time iteration
- A Real-Time Iteration Scheme for Nonlinear Optimization in Optimal Feedback Control
- A Lyapunov Function for Economic Optimizing Model Predictive Control
- An online active set strategy to overcome the limitations of explicit MPC
- Object-oriented software for quadratic programming
- Autogenerating microsecond solvers for nonlinear MPC: A tutorial using ACADO integrators
- FORCES NLP
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