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 41 articles , 1 standard article )

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  1. Buşoniu, Lucian; Páll, Előd; Munos, Rémi: Continuous-action planning for discounted infinite-horizon nonlinear optimal control with Lipschitz values (2018)
  2. Gaitsgory, Vladimir; Grüne, Lars; Höger, Matthias; Kellett, Christopher M.; Weller, Steven R.: Stabilization of strictly dissipative discrete time systems with discounted optimal control (2018)
  3. Houska, Boris; Li, Jiaqi C.; Chachuat, Beno^ıt: Towards rigorous robust optimal control via generalized high-order moment expansion (2018)
  4. Kouzoupis, Dimitris; Frison, Gianluca; Zanelli, Andrea; Diehl, Moritz: Recent advances in quadratic programming algorithms for nonlinear model predictive control (2018)
  5. Nicholson, Bethany; Siirola, John D.; Watson, Jean-Paul; Zavala, Victor M.; Biegler, Lorenz T.: pyomo.dae: a modeling and automatic discretization framework for optimization with differential and algebraic equations (2018)
  6. Putkaradze, Vakhtang; Rogers, Stuart: Constraint control of nonholonomic mechanical systems (2018)
  7. Quirynen, Rien; Gros, Sébastien; Diehl, Moritz: Inexact Newton-type optimization with iterated sensitivities (2018)
  8. Faulwasser, Timm; Korda, Milan; Jones, Colin N.; Bonvin, Dominique: On turnpike and dissipativity properties of continuous-time optimal control problems (2017)
  9. Kratochvíl, Václav; Vomlel, Jiří: Influence diagrams for speed profile optimization (2017)
  10. Mazen Alamir: The pdf-mpc Package: A Free-Matlab-Coder package for Real-Time Nonlinear Model Predictive Control (2017) arXiv
  11. Quirynen, Rien: Numerical simulation methods for embedded optimization (2017)
  12. Quirynen, Rien; Gros, Sébastien; Houska, Boris; Diehl, Moritz: Lifted collocation integrators for direct optimal control in ACADO toolkit (2017)
  13. Schürmann, Bastian; Althoff, Matthias: Convex interpolation control with formal guarantees for disturbed and constrained nonlinear systems (2017)
  14. 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)
  15. Käpernick, Bartosz; Graichen, Knut: Nonlinear model predictive control based on constraint transformation (2016)
  16. Rachah, Amira; Torres, Delfim F. M.: Dynamics and optimal control of Ebola transmission (2016)
  17. Alamir, Mazen: On probabilistic certification of combined cancer therapies using strongly uncertain models (2015)
  18. Françolin, Camila C.; Benson, David A.; Hager, William W.; Rao, Anil V.: Costate approximation in optimal control using integral Gaussian quadrature orthogonal collocation methods (2015)
  19. Houska, Boris: Enforcing asymptotic orbital stability of economic model predictive control (2015)
  20. 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)

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