Revisiting the analysis of optimal control problems with several state constraints
The trust region affine interior point algorithm for convex and nonconvex quadratic programming
Second-order analysis for optimal control problems with pure state constraints and mixed control-state constraints
Explicit polyhedral approximation of the Euclidean ball
We discuss the problem of computing points of whose convex hull contains the Euclidean ball, and is contained in a small multiple of it. Given a polytope containing the Euclidean ball, we introduce its successor obtained by intersection with all tangent spaces to the Euclidean ball, whose normals point towards the vertices of the polytope. Starting from the ball, we discuss the computation of the two first successors, and give a complete analysis...
A fast algorithm for the two dimensional HJB equation of stochastic control
This paper analyses the implementation of the generalized finite differences method for the HJB equation of stochastic control, introduced by two of the authors in [Bonnans and Zidani, SIAM J. Numer. Anal. 41 (2003) 1008–1021]. The computation of coefficients needs to solve at each point of the grid (and for each control) a linear programming problem. We show here that, for two dimensional problems, this linear programming problem can be solved in operations, where is the size of the stencil....
Second-order sufficient conditions for strong solutions to optimal control problems
In this article, given a reference feasible trajectory of an optimal control problem, we say that the quadratic growth property for bounded strong solutions holds if the cost function of the problem has a quadratic growth over the set of feasible trajectories with a bounded control and with a state variable sufficiently close to the reference state variable. Our sufficient second-order optimality conditions in Pontryagin form ensure this property and ensure that the reference trajectory is a bounded...
A fast algorithm for the two dimensional HJB equation of stochastic control
This paper analyses the implementation of the generalized finite differences method for the HJB equation of stochastic control, introduced by two of the authors in [Bonnans and Zidani, (2003) 1008–1021]. The computation of coefficients needs to solve at each point of the grid (and for each control) a linear programming problem. We show here that, for two dimensional problems, this linear programming problem can be solved in operations, where ...
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