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AUTOMATICA
2006
113views more  AUTOMATICA 2006»
13 years 4 months ago
Least costly identification experiment for control
All approaches to optimal experiment design for control have so far focused on deriving an input signal (or input signal spectrum) that minimizes some control-oriented measure of ...
Xavier Bombois, Gérard Scorletti, Michel Ge...
JAIR
2002
163views more  JAIR 2002»
13 years 4 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
SIAMCO
2000
123views more  SIAMCO 2000»
13 years 4 months ago
Adaptive LQG Control of Input-Output Systems---A Cost-biased Approach
In this paper, we consider linear systems in input-output form and introduce a new adaptive linear quadratic Gaussian (LQG) control scheme which is shown to be self-optimizing. The...
Maria Prandini, Marco C. Campi
CDC
2010
IEEE
122views Control Systems» more  CDC 2010»
12 years 11 months ago
On optimal input design in system identification for control
Abstract-- This paper considers a recently proposed framework for experiment design in system identification for control. We will consider model based control design methods, such ...
Bo Wahlberg, Håkan Hjalmarsson, Mariette Ann...
CEC
2009
IEEE
13 years 8 months ago
Automatic system identification based on coevolution of models and tests
In evolutionary robotics, controllers are often designed in simulation, then transferred onto the real system. Nevertheless, when no accurate model is available, controller transfe...
Sylvain Koos, Jean-Baptiste Mouret, Stéphan...