Lyapunov methods in nonsmooth optimization. Part II: Persistently exciting finite differences

Author

Teel, Andrew R.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA

Volume

1

fYear

2000

fDate

2000

Firstpage

118

Abstract

For Part I see ibid. (2000). A recent converse Lyapunov theorem for differential inclusions is used to generate a class of finite difference algorithms for nonsmooth optimization. The algorithms rely on a proof of asymptotic stability for differential inclusions that contain persistently exciting signals and the ability to approximate these differential inclusions with finite differences. The notion of persistency of excitation that is used here generalizes that which is typically used in the identification and adaptive control literature

Keywords

Lyapunov methods; adaptive control; asymptotic stability; identification; nonlinear programming; Lyapunov methods; adaptive control; asymptotic stability; finite differences; identification; nonlinear programming; nonsmooth optimization; Adaptive control; Algorithm design and analysis; Asymptotic stability; Convergence; Finite difference methods; Functional programming; Lyapunov method; Minimization methods; Optimization methods; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2000. Proceedings of the 39th IEEE Conference on

Conference_Location

Sydney, NSW

ISSN

0191-2216

Print_ISBN

0-7803-6638-7

Type

conf

DOI

10.1109/CDC.2000.912743

Filename

912743