Title :
Nonlinear estimation using Mean Field Games
Author :
Pequito, Sergio ; Aguiar, A. Pedro ; Sinopoli, Bruno ; Gomes, Diogo A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Tech. Univ. of Lisbon, Lisbon, Portugal
Abstract :
This paper introduces Mean Field Games (MFG) as a framework to develop optimal estimators in some sense for a general class of nonlinear systems. We show that under suitable conditions the estimation error converges exponentially fast to zero. Computer simulations are performed to illustrate the method. In particular we provide an example where the proposed estimator converges whereas both extended Kalman filter and particle filter diverge.
Keywords :
Kalman filters; game theory; nonlinear estimation; particle filtering (numerical methods); MFG; extended Kalman filter; mean field games; nonlinear estimation; optimal estimator; particle filter; Convergence; Cost function; Equations; Estimation; Games; Kalman filters; Mathematical model;
Conference_Titel :
Network Games, Control and Optimization (NetGCooP), 2011 5th International Conference on
Conference_Location :
Paris
Print_ISBN :
978-1-4673-0383-5
