Abstract

In this paper a generalization of the indirect pseudo-spectral method, presented in [17], for the numerical solution of budget-constrained infinite horizon optimal control problems is presented. Consideration of the problem statement in the framework of weighted functional spaces allows to arrive at a good approximation for the initial value of the adjoint variable, which is inevitable for obtaining good numerical solutions. The presented method is illustrated by applying it to the budget-constrained linear-quadratic regulator model. The quality of approximate solutions is demonstrated by an example.

Highlights

  • In the last decades, developing numerical solution methods for infinite horizon optimal control problems has emerged a lot of attention and a plenty of new results were obtained, cf. [5], [7], [9], [17]

  • We intend to describe an indirect numerical solution method, i.e. it acts according to the scheme ”first optimize, discretize”, and represents an extended version of the indirect pseudospectral method presented in [17], for a class of budget-constrained infinite horizon optimal control problems

  • We do not provide a rigorous convergence result of the suggested pseudospectral method here, the results observed above as well as solutions for other optimal control problems provided by pseudo-spectral method such as inverse pendulum problem or Lotka-Volterra optimal control problem, cf. [1], allow us to assume that the chosen strategy would lead to comparable convergence results for other budgetconstrained optimal control problems

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Summary

Introduction

In the last decades, developing numerical solution methods for infinite horizon optimal control problems has emerged a lot of attention and a plenty of new results were obtained, cf. [5], [7], [9], [17]. Among them, both direct and indirect solution methods were established. We extend the indirect pseudospectral method, introduced in [17], onto the class of budget-constrained infinite horizon optimal control problems.

Definitions of weighted functional spaces
Problem statement
Necessary optimality conditions
Description of the method
Conclusions
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