Optimization of continuous-time systems with constraints: controller design using the Hamilton-Jacobi-Bellman theory

Author

Lyashevskiy, Sergey ; Chen, Yaobin

Author_Institution

Dept. of Electr. Eng., Purdue Univ., Indianapolis, IN, USA

Volume

2

fYear

1996

fDate

11-13 Dec 1996

Firstpage

1331

Abstract

We treat optimization issues for linear continuous-time systems whose states and control are bounded. The objective of this paper is to design a nonlinear full state feedback control algorithm that satisfies the constraints by minimizing nonquadratic costs. The fundamental ideas involve the application of nonquadratic functionals and approximation of the Hamilton-Jacobi-Bellman (HJB) equation using nonquadratic return functions. Utilizing necessary and sufficient conditions, a solution for the constrained optimization problem is found and an optimal control law in the closed form is designed

Keywords

continuous time systems; control system synthesis; dynamic programming; functional equations; linear systems; minimisation; optimal control; set theory; state feedback; Hamilton-Jacobi-Bellman theory; constrained optimization problem; controller design; linear continuous-time systems; necessary and sufficient conditions; nonlinear full state feedback control algorithm; nonquadratic costs; nonquadratic functionals; nonquadratic return functions; optimal control law; optimization issues; Algorithm design and analysis; Constraint optimization; Control system synthesis; Control systems; Costs; Design optimization; Jacobian matrices; Nonlinear equations; State feedback; Sufficient conditions;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1996., Proceedings of the 35th IEEE Conference on

Conference_Location

Kobe

ISSN

0191-2216

Print_ISBN

0-7803-3590-2

Type

conf

DOI

10.1109/CDC.1996.572686

Filename

572686