ACADO Toolkit is a software environment and algorithm collection for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control, including model predictive control, state and parameter estimation and robust optimization. ACADO Toolkit is implemented as self-contained C++ code and comes along with user-friendly MATLAB interface. The object-oriented design allows for convenient coupling of existing optimization packages and for extending it with user-written optimization routines.

References in zbMATH (referenced in 24 articles , 1 standard article )

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  1. Quirynen, Rien: Numerical simulation methods for embedded optimization (2017)
  2. Alessandretti, Andrea; Aguiar, A.Pedro; Jones, Colin N.: On convergence and performance certification of a continuous-time economic model predictive control scheme with time-varying performance index (2016)
  3. Rachah, Amira; Torres, Delfim F.M.: Dynamics and optimal control of Ebola transmission (2016)
  4. Alamir, Mazen: On probabilistic certification of combined cancer therapies using strongly uncertain models (2015)
  5. Houska, Boris: Enforcing asymptotic orbital stability of economic model predictive control (2015)
  6. Houska, Boris; Telen, Dries; Logist, Filip; Diehl, Moritz; Van Impe, Jan F.M.: An economic objective for the optimal experiment design of nonlinear dynamic processes (2015)
  7. Houska, Boris; Villanueva, Mario E.; Chachuat, Beno^ıt: Stable set-valued integration of nonlinear dynamic systems using affine set-parameterizations (2015)
  8. Quirynen, Rien; Vukov, Milan; Diehl, Moritz: Multiple shooting in a microsecond (2015)
  9. Quirynen, R.; Vukov, M.; Zanon, M.; Diehl, M.: Autogenerating microsecond solvers for nonlinear MPC: a tutorial using ACADO integrators (2015)
  10. Tchoń, Krzysztof; Ratajczak, Adam; Góral, Ida: Lagrangian Jacobian inverse for nonholonomic robotic systems (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. Faulwasser, Timm; Hagenmeyer, Veit; Findeisen, Rolf: Constrained reachability and trajectory generation for flat systems (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. Houska, Boris; Chachuat, Beno^ıt: Branch-and-lift algorithm for deterministic global optimization in nonlinear optimal control (2014)
  15. Kaya, C.Yalçın; Maurer, Helmut: A numerical method for nonconvex multi-objective optimal control problems (2014)
  16. Müller, Matthias A.; Angeli, David; Allgöwer, Frank: Transient average constraints in economic model predictive control (2014)
  17. Müller, Matthias A.; Angeli, David; Allgöwer, Frank; Amrit, Rishi; Rawlings, James B.: Convergence in economic model predictive control with average constraints (2014)
  18. Word, Daniel P.; Kang, Jia; Akesson, Johan; Laird, Carl D.: Efficient parallel solution of large-scale nonlinear dynamic optimization problems (2014)
  19. Houska, Boris; Diehl, Moritz: Nonlinear robust optimization via sequential convex bilevel programming (2013)
  20. Logist, Filip; van Impe, Jan: Novel insights for multi-objective optimisation in engineering using normal boundary intersection and (enhanced) normalised normal constraint (2012)

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