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 41 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. Huber, Andreas; Gerdts, Matthias; Bertolazzi, Enrico: Structure exploitation in an interior-point method for fully discretized, state constrained optimal control problems (2018)
  3. Korda, Milan; Mezić, Igor: Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control (2018)
  4. Kouzoupis, Dimitris; Frison, Gianluca; Zanelli, Andrea; Diehl, Moritz: Recent advances in quadratic programming algorithms for nonlinear model predictive control (2018)
  5. Quirynen, Rien; Gros, Sébastien; Diehl, Moritz: Inexact Newton-type optimization with iterated sensitivities (2018)
  6. Koehler, Sarah; Danielson, Claus; Borrelli, Francesco: A primal-dual active-set method for distributed model predictive control (2017)
  7. Quirynen, Rien; Gros, Sébastien; Houska, Boris; Diehl, Moritz: Lifted collocation integrators for direct optimal control in ACADO toolkit (2017)
  8. Šantin, Ondřej; Jarošová, Marta; Havlena, Vladimír; Dostál, Zdeněk: Proportioning with second-order information for model predictive control (2017)
  9. Verschueren, Robin; Zanon, Mario; Quirynen, Rien; Diehl, Moritz: A sparsity preserving convexification procedure for indefinite quadratic programs arising in direct optimal control (2017)
  10. Zanon, Mario; Boccia, Andrea; Palma, Vryan Gil S.; Parenti, Sonja; Xausa, Ilaria: Direct optimal control and model predictive control (2017)
  11. Forsgren, Anders; Gill, Philip E.; Wong, Elizabeth: Primal and dual active-set methods for convex quadratic programming (2016)
  12. Janka, Dennis; Kirches, Christian; Sager, Sebastian; Wächter, Andreas: An SR1/BFGS SQP algorithm for nonconvex nonlinear programs with block-diagonal Hessian matrix (2016)
  13. Curtis, Frank E.; Han, Zheng; Robinson, Daniel P.: A globally convergent primal-dual active-set framework for large-scale convex quadratic optimization (2015)
  14. Frasch, Janick V.; Sager, Sebastian; Diehl, Moritz: A parallel quadratic programming method for dynamic optimization problems (2015)
  15. Gill, Philip E.; Wong, Elizabeth: Methods for convex and general quadratic programming (2015)
  16. Janka, Dennis: Sequential quadratic programming with indefinite Hessian approximations for nonlinear optimum experimental design for parameter estimation in differential-algebraic equations (2015)
  17. Janka, Dennis; Körkel, Stefan; Bock, Hans Georg: Direct multiple shooting for nonlinear optimum experimental design (2015)
  18. Johnson, Travis C.; Kirches, Christian; Wächter, Andreas: An active-set method for quadratic programming based on sequential hot-starts (2015)
  19. Necoara, Ion; Patrascu, Andrei; Nedić, Angelia: Complexity certifications of first-order inexact Lagrangian methods for general convex programming: application to real-time MPC (2015)
  20. Quirynen, Rien; Vukov, Milan; Diehl, Moritz: Multiple shooting in a microsecond (2015)

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