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 30 articles )

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  1. Forsgren, Anders; Gill, Philip E.; Wong, Elizabeth: Primal and dual active-set methods for convex quadratic programming (2016)
  2. Curtis, Frank E.; Han, Zheng; Robinson, Daniel P.: A globally convergent primal-dual active-set framework for large-scale convex quadratic optimization (2015)
  3. Frasch, Janick V.; Sager, Sebastian; Diehl, Moritz: A parallel quadratic programming method for dynamic optimization problems (2015)
  4. Gill, Philip E.; Wong, Elizabeth: Methods for convex and general quadratic programming (2015)
  5. Janka, Dennis: Sequential quadratic programming with indefinite Hessian approximations for nonlinear optimum experimental design for parameter estimation in differential-algebraic equations (2015)
  6. Janka, Dennis; Körkel, Stefan; Bock, Hans Georg: Direct multiple shooting for nonlinear optimum experimental design (2015)
  7. Johnson, Travis C.; Kirches, Christian; Wächter, Andreas: An active-set method for quadratic programming based on sequential hot-starts (2015)
  8. Necoara, Ion; Patrascu, Andrei; Nedić, Angelia: Complexity certifications of first-order inexact Lagrangian methods for general convex programming: application to real-time MPC (2015)
  9. Quirynen, Rien; Vukov, Milan; Diehl, Moritz: Multiple shooting in a microsecond (2015)
  10. Shekhar, Rohan C.; Manzie, Chris: Optimal move blocking strategies for model predictive control (2015)
  11. Telen, Dries; Van Riet, Nick; Logist, Flip; Van Impe, Jan: A differentiable reformulation for E-optimal design of experiments in nonlinear dynamic biosystems (2015)
  12. Buerger, Johannes; Cannon, Mark; Kouvaritakis, Basil: An active set solver for input-constrained robust receding horizon control (2014)
  13. Ferreau, Hans Joachim; Kirches, Christian; Potschka, Andreas; Bock, Hans Georg; Diehl, Moritz: qpOASES: a parametric active-set algorithm for quadratic programming (2014)
  14. Kungurtsev, Vyacheslav; Diehl, Moritz: Sequential quadratic programming methods for parametric nonlinear optimization (2014)
  15. Zeilinger, Melanie N.; Raimondo, Davide M.; Domahidi, Alexander; Morari, Manfred; Jones, Colin N.: On real-time robust model predictive control (2014)
  16. Ali, Sofiane Ahmed; Langlois, Nicolas: Sliding mode control for diesel engine air path subject to matched and unmatched disturbances using extended state observer (2013)
  17. Yang, Ting; Karimi, Hamid Reza: LMI-based model predictive control for a class of constrained uncertain fuzzy Markov jump systems (2013)
  18. Andersson, Joel; Åkesson, Johan; Diehl, Moritz: CasADi: A symbolic package for automatic differentiation and optimal control (2012)
  19. Huyck, Bart; Ferreau, Hans Joachim; Diehl, Moritz; De Brabanter, Jos; Van Impe, Jan F.M.; De Moor, Bart; Logist, Filip: Towards online model predictive control on a programmable logic controller: practical considerations (2012)
  20. Pistikopoulos, Efstratios N.; Dominguez, Luis; Panos, Christos; Kouramas, Konstantinos; Chinchuluun, Altannar: Theoretical and algorithmic advances in multi-parametric programming and control (2012)

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