DocumentCode :
404582
Title :
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
Link To Document :
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