qpDUNES is quadratic programming solver targeted at block-banded convex QPs that arise in optimal control, dynamic optimization, and estimation. The acronym DUNES stands for dual Newton strategy, the novel solution methodology which this solver implements. See this publication for the mathematical details. qpDUNES is a plain, self-contained C code written according to the C90 standard to enlarge compatibility with embedded hardware platforms. It comes with its own linear algebra module and efficient data storage formats to better exploit the problem intrinsic structures. Problems can be set up and solved from a C/C++ environment as well as conveniently from MATLAB. qpDUNES provides setup and solve routines (both cold- and warm-started) for multi-stage QPs, as well as for linear time-invariant (LTI) and for linear time-varying (LTV) model-predictive control problems in both environments. For nonlinear model predictive control and moving horizon estimation, the powerful ACADO Toolkit features an interface to use qpDUNES as its workhorse.

References in zbMATH (referenced in 15 articles , 1 standard article )

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  1. Deng, Haoyang; Ohtsuka, Toshiyuki: ParNMPC -- a parallel optimisation toolkit for real-time nonlinear model predictive control (2022)
  2. Verschueren, Robin; Frison, Gianluca; Kouzoupis, Dimitris; Frey, Jonathan; van Duijkeren, Niels; Zanelli, Andrea; Novoselnik, Branimir; Albin, Thivaharan; Quirynen, Rien; Diehl, Moritz: \textttacados-- a modular open-source framework for fast embedded optimal control (2022)
  3. Gros, Sébastien; Zanon, Mario; Quirynen, Rien; Bemporad, Alberto; Diehl, Moritz: From linear to nonlinear MPC: bridging the gap via the real-time iteration (2020)
  4. Liao-McPherson, Dominic; Kolmanovsky, Ilya: FBstab: a proximally stabilized semismooth algorithm for convex quadratic programming (2020)
  5. Deng, Haoyang; Ohtsuka, Toshiyuki: A parallel Newton-type method for nonlinear model predictive control (2019)
  6. Kouzoupis, Dimitris; Frison, Gianluca; Zanelli, Andrea; Diehl, Moritz: Recent advances in quadratic programming algorithms for nonlinear model predictive control (2018)
  7. Quirynen, Rien; Gros, Sébastien; Diehl, Moritz: Inexact Newton-type optimization with iterated sensitivities (2018)
  8. Curtis, Frank E.; Raghunathan, Arvind U.: Solving nearly-separable quadratic optimization problems as nonsmooth equations (2017)
  9. Klintberg, Emil; Gros, Sebastien: Numerical structure of the Hessian of the Lagrange dual function for a class of convex problems (2017)
  10. Quirynen, Rien; Gros, Sébastien; Houska, Boris; Diehl, Moritz: Lifted collocation integrators for direct optimal control in ACADO toolkit (2017)
  11. Verschueren, Robin; Zanon, Mario; Quirynen, Rien; Diehl, Moritz: A sparsity preserving convexification procedure for indefinite quadratic programs arising in direct optimal control (2017)
  12. Houska, Boris; Frasch, Janick; Diehl, Moritz: An augmented Lagrangian based algorithm for distributed nonconvex optimization (2016)
  13. Frasch, Janick V.; Sager, Sebastian; Diehl, Moritz: A parallel quadratic programming method for dynamic optimization problems (2015)
  14. Quirynen, Rien; Vukov, Milan; Diehl, Moritz: Multiple shooting in a microsecond (2015)
  15. Quirynen, R.; Vukov, M.; Zanon, M.; Diehl, M.: Autogenerating microsecond solvers for nonlinear MPC: a tutorial using ACADO integrators (2015)