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.

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  1. Nath, Bhagya Jyoti; Sarmah, Hemanta Kumar; Maurer, Helmut: An optimal control strategy for antiretroviral treatment of HIV infection in presence of immunotherapy (2022)
  2. Pager, Elisha R.; Rao, Anil V.: Method for solving bang-bang and singular optimal control problems using adaptive Radau collocation (2022)
  3. Berahas, Albert S.; Curtis, Frank E.; Robinson, Daniel; Zhou, Baoyu: Sequential quadratic optimization for nonlinear equality constrained stochastic optimization (2021)
  4. Botkin, Nikolai; Turova, Varvara; Hosseini, Barzin; Diepolder, Johannes; Holzapfel, Florian: Tracking aircraft trajectories in the presence of wind disturbances (2021)
  5. Djema, Walid; Giraldi, Laetitia; Maslovskaya, Sofya; Bernard, Olivier: \textitTurnpikefeatures in optimal selection of species represented by quota models (2021)
  6. Eide, Joseph D.; Hager, William W.; Rao, Anil V.: Modified Legendre-Gauss-Radau collocation method for optimal control problems with nonsmooth solutions (2021)
  7. Gabiccini, M.; Bartali, L.; Guiggiani, M.: Analysis of driving styles of a GP2 car via minimum lap-time direct trajectory optimization (2021)
  8. Goverde, Rob M. P.; Scheepmaker, Gerben M.; Wang, Pengling: Pseudospectral optimal train control (2021)
  9. Kielas-Jensen, Calvin; Cichella, Venanzio; Casbeer, David; Manyam, Satyanarayana Gupta; Weintraub, Isaac: Persistent monitoring by multiple unmanned aerial vehicles using Bernstein polynomials (2021)
  10. Lohéac, Jérôme; Trélat, Emmanuel; Zuazua, Enrique: Nonnegative control of finite-dimensional linear systems (2021)
  11. Lv, Lu; Liu, Xinggao; Xiao, Long; Ma, Weihua; Qi, Zhenqiang; Ye, Song; Xu, Guoqiang; Zheng, Zongzhun; Wang, Sen; Zhang, Zeyin: A novel non-uniform optimal control approach for hypersonic cruise vehicle with waypoint and no-fly zone constraints (2021)
  12. Mehrpouya, Mohammad Ali; Peng, Haijun: A robust pseudospectral method for numerical solution of nonlinear optimal control problems (2021)
  13. Pablos, Blanca; Gerdts, Matthias: Substructure exploitation of a nonsmooth Newton method for large-scale optimal control problems with full discretization (2021)
  14. Parvathy, Prasanna; Jacob, Jeevamma: Inverse optimal control via diagonal stabilization applied to attitude tracking of a reusable launch vehicle (2021)
  15. Robuschi, Nicolò; Zeile, Clemens; Sager, Sebastian; Braghin, Francesco: Multiphase mixed-integer nonlinear optimal control of hybrid electric vehicles (2021)
  16. Settati, A.; Lahrouz, A.; Zahri, M.; Tridane, A.; El Fatini, M.; El Mahjour, H.; Seaid, M.: A stochastic threshold to predict extinction and persistence of an epidemic SIRS system with a general incidence rate (2021)
  17. Singh, Vyoma; Pal, Birupaksha; Jain, Tushar: Integrated methodology for state and parameter estimation of spark-ignition engines (2021)
  18. Xu, Ying-tao; Zhang, Ying; Lv, Zhen-hong: Optimal control of a quality supervision profit model for the electronic intermediary (2021)
  19. Zarepour, Mazyar; Loghmani, Ghasem Barid: Numerical solution of arbitrary-order linear partial differential equations using an optimal control technique (2021)
  20. Bastos, Guaraci jun.; Brüls, Olivier: Analysis of open-loop control design and parallel computation for underactuated manipulators (2020)

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