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 71 articles , 2 standard articles )

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  1. Berret, Bastien; Jean, Frédéric: Efficient computation of optimal open-loop controls for stochastic systems (2020)
  2. Betts, John T.; Campbell, Stephen L.; Digirolamo, Claire: Initial guess sensitivity in computational optimal control problems (2020)
  3. Cardona-Salgado, Daiver; Campo-Duarte, Doris E.; Sepulveda-Salcedo, Lilian S.; Vasilieva, Olga: \textitWolbachia-based biocontrol for dengue reduction using dynamic optimization approach (2020)
  4. Jansen, Conor; McPhee, John: Predictive dynamic simulation of olympic track cycling standing start using direct collocation optimal control (2020)
  5. Zhao, Jisong; Li, Shuang: Adaptive mesh refinement method for solving optimal control problems using interpolation error analysis and improved data compression (2020)
  6. Campbell, Stephen; Kunkel, Peter: General nonlinear differential algebraic equations and tracking problems: a robotics example (2019)
  7. Hager, William W.; Hou, Hongyan; Mohapatra, Subhashree; Rao, Anil V.; Wang, Xiang-Sheng: Convergence rate for a Radau hp collocation method applied to constrained optimal control (2019)
  8. Ha, Jung-Su; Choi, Han-Lim: On periodic optimal solutions of persistent sensor planning for continuous-time linear systems (2019)
  9. Hu, Xiaochuan; Ke, Guoyi; Jang, Sophia R.-J.: Modeling pancreatic cancer dynamics with immunotherapy (2019)
  10. Pei, Pei; Wang, Jiang: Near-optimal guidance with impact angle and velocity constraints using sequential convex programming (2019)
  11. Wang, Pengling; Goverde, Rob M. P.: Multi-train trajectory optimization for energy-efficient timetabling (2019)
  12. Wan, Shizheng; Chang, Xiaofei; Li, Quancheng; Yan, Jie: Finite-horizon optimal tracking guidance for aircraft based on approximate dynamic programming (2019)
  13. Williams, Nakeya D.; Mehlsen, Jesper; Tran, Hien T.; Olufsen, Mette S.: An optimal control approach for blood pressure regulation during head-up tilt (2019)
  14. Bichiou, Salim; Bouafoura, Mohamed Karim; Benhadj Braiek, Naceur: Time optimal control laws for bilinear systems (2018)
  15. Campo-Duarte, Doris E.; Vasilieva, Olga; Cardona-Salgado, Daiver; Svinin, Mikhail: Optimal control approach for establishing wMelpop Wolbachia infection among wild Aedes aegypti populations (2018)
  16. Chen, Qi; Wang, Xugang; Yang, Jing: Optimal path-following guidance with generalized weighting functions based on indirect Gauss pseudospectral method (2018)
  17. Elgindy, Kareem T.: Optimal control of a parabolic distributed parameter system using a fully exponentially convergent barycentric shifted Gegenbauer integral pseudospectral method (2018)
  18. Jason K. Moore; Antonie van den Bogert: opty: Software for trajectory optimization and parameter identification using direct collocation (2018) not zbMATH
  19. Mir, Imran; Taha, Haitham; Eisa, Sameh A.; Maqsood, Adnan: A controllability perspective of dynamic soaring (2018)
  20. Nicholson, Bethany; Siirola, John D.; Watson, Jean-Paul; Zavala, Victor M.; Biegler, Lorenz T.: \textttpyomo.dae: a modeling and automatic discretization framework for optimization with differential and algebraic equations (2018)

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