TY - GEN
T1 - Hybrid identification of time-varying parameter with particle filtering and expectation maximization
AU - Hartmann, András
AU - Vinga, Susana
AU - Lemos, João M.
PY - 2013
Y1 - 2013
N2 - The problem of time-varying parameter identification is considered on a class of nonlinear hybrid systems. It is assumed that inputs and outputs are directly measured, and a subset of system parameters can take different values from a finite set at each time instance. An offline (batch) algorithm that combines particle filtering and the expectation maximization is introduced for the identification of such systems. The efficiency of the proposed method is illustrated through simulated examples.
AB - The problem of time-varying parameter identification is considered on a class of nonlinear hybrid systems. It is assumed that inputs and outputs are directly measured, and a subset of system parameters can take different values from a finite set at each time instance. An offline (batch) algorithm that combines particle filtering and the expectation maximization is introduced for the identification of such systems. The efficiency of the proposed method is illustrated through simulated examples.
UR - http://www.scopus.com/inward/record.url?scp=84885205735&partnerID=8YFLogxK
U2 - 10.1109/MED.2013.6608826
DO - 10.1109/MED.2013.6608826
M3 - Conference contribution
AN - SCOPUS:84885205735
SN - 9781479909971
T3 - 2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Conference Proceedings
SP - 884
EP - 889
BT - 2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Conference Proceedings
T2 - 2013 21st Mediterranean Conference on Control and Automation, MED 2013
Y2 - 25 June 2013 through 28 June 2013
ER -