Randomized algorithms in robust control

Author

Calafiore, Giuseppe ; Dabbene, Fabrizio ; Tempo, Roberto

Author_Institution

Dipartimento di Autom. e Informatica, Politecnico di Torino, Italy

Volume

2

fYear

2003

fDate

9-12 Dec. 2003

Firstpage

1908

Abstract

The probabilistic approach to analysis and design of robust control systems is an emerging philosophy that gained increasing interest in the past. Opposed to the so-far dominating paradigm of deterministic worst-case robustness, the probabilistic approach presents itself as a natural tool to deal with the random character of uncertainties affecting control systems. In this paper, we discuss randomized algorithms for probabilistic robustness, with particular attention to recently developed methodologies for controller synthesis.

Keywords

computational complexity; control system synthesis; convergence; deterministic algorithms; gradient methods; learning (artificial intelligence); probability; randomised algorithms; robust control; stochastic processes; controller design; controller synthesis; convergence; deterministic worst-case robustness; probabilistic approach; randomized algorithms; robust control systems; statistical learning theory; stochastic gradients; Algorithm design and analysis; Books; Control system synthesis; Control systems; Ear; Probability; Robust control; Robustness; Stochastic processes; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2003. Proceedings. 42nd IEEE Conference on

ISSN

0191-2216

Print_ISBN

0-7803-7924-1

Type

conf

DOI

10.1109/CDC.2003.1272894

Filename

1272894