Sparse Optimal Control Software (SOCS). The Sparse Optimal Control Family, developed by The Boeing Company, contains two advanced software packages, available separately or together. Sparse Optimal Control Software (SOCS) is general-purpose software for solving optimal control problems. Applications include trajectory optimization, chemical process control and machine tool path definition. Sparse Nonlinear Programming exploits state-of-the-art sparse linear algebra technology to solve very large optimization problems orders of magnitude faster than traditional methods. Applications with more than 100,000 variables and constraints can now be solved efficiently on desktop computers. The Sparse Nonlinear Programming software is available as an integral part of SOCS or as a separate package.

References in zbMATH (referenced in 78 articles )

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  1. Quirynen, Rien; Gros, Sébastien; Diehl, Moritz: Inexact Newton-type optimization with iterated sensitivities (2018)
  2. Bara, O.; Djouadi, S.M.; Day, J.D.; Lenhart, S.: Immune therapeutic strategies using optimal controls with $L^1$ and $L^2$ type objectives (2017)
  3. Copp, David A.; Hespanha, João P.: Simultaneous nonlinear model predictive control and state estimation (2017)
  4. Dutra, Dimas Abreu Archanjo; Teixeira, Bruno Otávio Soares; Aguirre, Luis Antonio: Joint maximum \ita posteriori state path and parameter estimation in stochastic differential equations (2017)
  5. Ge, Ming; Kerrigan, Eric C.: Noise covariance identification for nonlinear systems using expectation maximization and moving horizon estimation (2017)
  6. Lohéac, Jér^ome; Trélat, Emmanuel; Zuazua, Enrique: Minimal controllability time for the heat equation under unilateral state or control constraints (2017)
  7. Betts, John T.; Campbell, Stephen L.; Thompson, Karmethia C.: Solving optimal control problems with control delays using direct transcription (2016)
  8. Boucher, Randy; Kang, Wei; Gong, Qi: Galerkin optimal control (2016)
  9. Campbell, Stephen; Kunkel, Peter: Solving higher index DAE optimal control problems (2016)
  10. Campbell, Stephen L.; Betts, John T.: Comments on direct transcription solution of DAE constrained optimal control problems with two discretization approaches (2016)
  11. 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)
  12. Chatterjee, Debasish; Nagahara, Masaaki; Quevedo, Daniel E.; Rao, K.S.Mallikarjuna: Characterization of maximum hands-off control (2016)
  13. Costa, Bertinho A.; Lemos, João M.: Optimal control of the temperature in a solar furnace (2016)
  14. Nikooeinejad, Z.; Delavarkhalafi, A.; Heydari, M.: A numerical solution of open-loop Nash equilibrium in nonlinear differential games based on Chebyshev pseudospectral method (2016)
  15. Rojas, Clara; Belmonte-Beitia, Juan; Pérez-García, Víctor M.; Maurer, Helmut: Dynamics and optimal control of chemotherapy for low grade gliomas: insights from a mathematical model (2016)
  16. Sukumar, Srikant; Chatterjee, Debasish: A jammer’s perspective of reachability and LQ optimal control (2016)
  17. Zhang, Ying; Yu, Changjun; Xu, Yingtao; Teo, Kok Lay: Minimizing control variation in discrete-time optimal control problems (2016)
  18. Zhu, Jiamin; Trélat, Emmanuel; Cerf, Max: Planar tilting maneuver of a spacecraft: singular arcs in the minimum time problem and chattering (2016)
  19. Zhu, Jiamin; Treĺat, Emmanuel; Cerf, Max: Minimum time control of the rocket attitude reorientation associated with orbit dynamics (2016)
  20. Berger, André; Grigoriev, Alexander; Peeters, Ralf; Usotskaya, Natalya: On time-optimal trajectories in non-uniform mediums (2015)

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