SQP Methods and their Application to Numerical Optimal Control

  • Alex Barclay
  • Philip E. Gill
  • J. Ben Rosen
Part of the International Series of Numerical Mathematics book series (ISNM, volume 124)


In recent years, sequential quadratic programming (SQP) methods have been developed that can reliably solve constrained optimization problems with many hundreds of variables and constraints. These methods require remarkably few evaluations of the problem functions and can be shown to converge to a solution under very mild conditions on the problem.

Some practical and theoretical aspects of applying SQP methods to optimal control problems are discussed, including the influence of the problem discretization and the zero/nonzero structure of the problem derivatives. We conclude with some recent approaches that tailor the SQP method to the control problem.


Optimal Control Problem Multiple Shooting Sequential Quadratic Programming Nonlinear Constraint Single Shooting 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Basel AG 1998

Authors and Affiliations

  • Alex Barclay
    • 1
  • Philip E. Gill
    • 1
  • J. Ben Rosen
    • 2
  1. 1.Department of MathematicsUniversity of CaliforniaSan Diego, La JollaUSA
  2. 2.Department of Computer Science and EngineeringUniversity of CaliforniaSan Diego, La JollaUSA

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