GPOPS-II - MATLAB Optimal Control Software. GPOPS-II is the next-generation of general purpose optimal control software. GPOPS-II is a new MATLAB software intended to solve general nonlinear optimal control problems (that is, problems where it is desired to optimize systems defined by differential-algebraic equations). GPOPS-II implements the new class of variable-order Gaussian quadrature methods. Using GPOPS-II, the continuous-time optimal control problem is transcribed to a nonlinear programming problem (NLP). The NLP is then solved using either the NLP solver SNOPT or the NLP solver IPOPT. GPOPS-II has been written by Michael A. Patterson and Anil V. Rao and represents a major advancement in the numerical solution of optimal control problems. GPOPS-II is available at NO CHARGE TO MEMBERS OF THE UNIVERSITY OF FLORIDA OR ANY U.S. FEDERAL GOVERNMENT INSTITUTION. All others are required to pay a licensing fee for using GPOPS-II. See also: Algorithm 902: GPOPS, A MATLAB software for solving multiple-phase optimal control problems using the gauss pseudospectral method. (Source:

This software is also peer reviewed by journal TOMS.

References in zbMATH (referenced in 37 articles , 2 standard articles )

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  1. Putkaradze, Vakhtang; Rogers, Stuart: Constraint control of nonholonomic mechanical systems (2018)
  2. Frego, Marco; Bertolazzi, Enrico; Biral, Francesco; Fontanelli, Daniele; Palopoli, Luigi: Semi-analytical minimum time solutions with velocity constraints for trajectory following of vehicles (2017)
  3. Kelly, Matthew: An introduction to trajectory optimization: how to do your own direct collocation (2017)
  4. Mall, Kshitij; Grant, Michael James: Epsilon-Trig regularization method for bang-bang optimal control problems (2017)
  5. Quirynen, Rien; Gros, Sébastien; Houska, Boris; Diehl, Moritz: Lifted collocation integrators for direct optimal control in ACADO toolkit (2017)
  6. Aykutlug, Erkut; Topcu, Ufuk; Mease, Kenneth D.: Manifold-following approximate solution of completely hypersensitive optimal control problems (2016)
  7. Betts, John T.; Campbell, Stephen L.; Thompson, Karmethia C.: Solving optimal control problems with control delays using direct transcription (2016)
  8. Campbell, Stephen; Kunkel, Peter: Solving higher index DAE optimal control problems (2016)
  9. Campbell, Stephen L.; Betts, John T.: Comments on direct transcription solution of DAE constrained optimal control problems with two discretization approaches (2016)
  10. Cannataro, Begüm Şenses; Rao, Anil V.; Davis, Timothy A.: State-defect constraint pairing graph coarsening method for Karush-Kuhn-Tucker matrices arising in orthogonal collocation methods for optimal control (2016)
  11. Merino, Enrique Guerrero; Duarte-Mermoud, Manuel A.: Online energy management for a solar car using pseudospectral methods for optimal control (2016)
  12. Sabeh, Z.; Shamsi, M.; Dehghan, Mehdi: Distributed optimal control of the viscous Burgers equation via a Legendre pseudo-spectral approach (2016)
  13. Choi, Han-Lim; Ha, Jung-Su: Informative windowed forecasting of continuous-time linear systems for mutual information-based sensor planning (2015)
  14. 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)
  15. Kamalapurkar, Rushikesh; Dinh, Huyen; Bhasin, Shubhendu; Dixon, Warren E.: Approximate optimal trajectory tracking for continuous-time nonlinear systems (2015)
  16. Li, Jing; Xi, Xiao-ning: Time-optimal reorientation of the rigid spacecraft using a pseudospectral method integrated homotopic approach (2015)
  17. Patterson, Michael A.; Hager, William W.; Rao, Anil V.: A $ph$ mesh refinement method for optimal control (2015)
  18. Ross, Steven M.; Cobb, Richard G.; Baker, William P.; Harmon, Frederick G.: Implementation lessons and pitfalls for real-time optimal control with stochastic systems (2015)
  19. Fernández, Luis A.; Pola, Cecilia: Catalog of the optimal controls in cancer chemotherapy for the Gompertz model depending on PK/PD and the integral constraint (2014)
  20. Pahlajani, Chetan D.; Sun, Jianxin; Poulakakis, Ioannis; Tanner, Herbert G.: Error probability bounds for nuclear detection: improving accuracy through controlled mobility (2014)

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