qpOASES

qpOASES – Online Active Set Strategy. qpOASES is an open-source C++ implementation of the recently proposed online active set strategy (see [Ferreau, 2006], [Ferreau et al., 2008]), which was inspired by important observations from the field of parametric quadratic programming. It has several theoretical features that make it particularly suited for model predictive control (MPC) applications. The software package qpOASES implements these ideas and has already been successfully used within industrial projects and, e.g., for closed-loop control of a real-world Diesel engine [Ferreau et al., 2007]. Recently, a couple of numerical modifications (as proposed in [Potschka et al., 2010]) have been implemented that greatly increase qpOASES’s reliability when solving semi-definite, ill-posed or degenerated convex QPs. (Source: http://plato.asu.edu)


References in zbMATH (referenced in 49 articles )

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  1. Andersson, Joel A. E.; Gillis, Joris; Horn, Greg; Rawlings, James B.; Diehl, Moritz: CasADi: a software framework for nonlinear optimization and optimal control (2019)
  2. Bian, Chentong; Zhu, Tong; Yin, Guodong; Xu, Liwei: Integrated speed planning and friction coefficient estimation algorithm for intelligent electric vehicles (2019)
  3. Englert, Tobias; Völz, Andreas; Mesmer, Felix; Rhein, Sönke; Graichen, Knut: A software framework for embedded nonlinear model predictive control using a gradient-based augmented Lagrangian approach (GRAMPC) (2019)
  4. Hose, Dominik; Hanss, Michael: Fuzzy linear least squares for the identification of possibilistic regression models (2019)
  5. Kouzoupis, D.; Klintberg, E.; Frison, G.; Gros, S.; Diehl, M.: A dual Newton strategy for tree-sparse quadratic programs and its implementation in the open-source software treeQP (2019)
  6. Otta, Pavel; Burant, Jiří; Šantin, Ondřej; Havlena, Vladimír: Newton projection with proportioning using iterative linear algebra for model predictive control with long prediction horizon (2019)
  7. Perne, Matija; Gerkšič, Samo; Pregelj, Boštjan: Soft inequality constraints in gradient method and fast gradient method for quadratic programming (2019)
  8. Wang, Guoqiang; Yu, Bo: PAL-Hom method for QP and an application to LP (2019)
  9. Huber, Andreas; Gerdts, Matthias; Bertolazzi, Enrico: Structure exploitation in an interior-point method for fully discretized, state constrained optimal control problems (2018)
  10. Korda, Milan; Mezić, Igor: Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control (2018)
  11. Kouzoupis, Dimitris; Frison, Gianluca; Zanelli, Andrea; Diehl, Moritz: Recent advances in quadratic programming algorithms for nonlinear model predictive control (2018)
  12. Nikolić, Milutin; Borovac, Branislav; Raković, Mirko: Dynamic balance preservation and prevention of sliding for humanoid robots in the presence of multiple spatial contacts (2018)
  13. Quirynen, Rien; Gros, Sébastien; Diehl, Moritz: Inexact Newton-type optimization with iterated sensitivities (2018)
  14. Koehler, Sarah; Danielson, Claus; Borrelli, Francesco: A primal-dual active-set method for distributed model predictive control (2017)
  15. Quirynen, Rien; Gros, Sébastien; Houska, Boris; Diehl, Moritz: Lifted collocation integrators for direct optimal control in ACADO toolkit (2017)
  16. Šantin, Ondřej; Jarošová, Marta; Havlena, Vladimír; Dostál, Zdeněk: Proportioning with second-order information for model predictive control (2017)
  17. Verschueren, Robin; Zanon, Mario; Quirynen, Rien; Diehl, Moritz: A sparsity preserving convexification procedure for indefinite quadratic programs arising in direct optimal control (2017)
  18. Zanon, Mario; Boccia, Andrea; Palma, Vryan Gil S.; Parenti, Sonja; Xausa, Ilaria: Direct optimal control and model predictive control (2017)
  19. Forsgren, Anders; Gill, Philip E.; Wong, Elizabeth: Primal and dual active-set methods for convex quadratic programming (2016)
  20. Janka, Dennis; Kirches, Christian; Sager, Sebastian; Wächter, Andreas: An SR1/BFGS SQP algorithm for nonconvex nonlinear programs with block-diagonal Hessian matrix (2016)

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