On interior-point Newton algorithms for discretized optimal control problems with state constraints∗

DOI10.1080/10556789808805679zbMath0903.49020OpenAlexW1991512592MaRDI QIDQ3839448

Luis Nunes Vicente

Publication date: 9 August 1998

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10556789808805679

zbMATH Keywords

state constraintsinterior-point algorithmsNewton's methodoptimality conditionsnonlinear programmingconstraint qualificationsoptimal control problemsaffine-scalingprimal dual

Mathematics Subject Classification ID

Large-scale problems in mathematical programming (90C06) Nonlinear programming (90C30) Numerical methods based on nonlinear programming (49M37)

Related Items (3)

A level set approach for the solution of a state-constrained optimal control problem ⋮ A trust region interior point algorithm for infinite dimensional nonlinear programming ⋮ An interior penalty method for optimal control problems with state and input constraints of nonlinear systems

Uses Software

• TRICE

Cites Work

• Interior point methods for optimal control of discrete time systems
• On the convergence of interior-reflective Newton methods for nonlinear minimization subject to bounds
• Superlinear and quadratic convergence of some primal - dual interior point methods for constrained optimization
• On the formulation and theory of the Newton interior-point method for nonlinear programming
• Newton's method for constrained optimization
• Projected Hessian Updating Algorithms for Nonlinearly Constrained Optimization
• On the Superlinear and Quadratic Convergence of Primal-Dual Interior Point Linear Programming Algorithms
• Projected Sequential Quadratic Programming Methods
• An Interior Trust Region Approach for Nonlinear Minimization Subject to Bounds

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