On Approaches for Solving Nonlinear Optimal Control Problems

被引：0
|
作者：
Boiko, Alina, V [1 ]
Smirnov, Nikolay, V [1 ]
机构：
[1] St Petersburg State Univ, 7-9 Univ Skaya Nab, St Petersburg 199034, Russia
来源：
INTELLIGENT DISTRIBUTED COMPUTING XIII | 2020年 / 868卷
关键词：
Optimal control; Gabasov's adaptive method; Dynamic programming method;
D O I：
10.1007/978-3-030-32258-8_21
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper discusses various approaches to solving nonlinear optimal control problems. Of all such approaches, we chose the two most characteristic. The first one uses sufficient conditions of optimality in the form of Hamilton-Jacobi-Bellman equations and the corresponding numerical method. The second is based on the reduction of optimal control problem to interval linear programming problem and finding a solution using the Gabasov's adaptive method. The main goal is to compare the capabilities of these methods within a specific problem of optimal control. As an application, we consider the problem of constructing optimal control in a nonlinear model of macroeconomic growth with nonlinear dynamical constraints. Comparative analysis of these two approaches and corresponding numerical simulation are presented.
引用
收藏
页码：183 / 188
页数：6
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