DocumentCode
176045
Title
Stochastic gradient algorithm for state space system with d-step delay
Author
Ya Gu ; Rui Ding
Author_Institution
Key Lab. of Adv. Process Control for Light Ind. (Minist. of Educ.), Jiangnan Univ., Wuxi, China
fYear
2014
fDate
May 31 2014-June 2 2014
Firstpage
1924
Lastpage
1928
Abstract
This paper researches parameter and state estimation problems for linear systems with d-step delay. Combining the linear transformation and the property of the shift operator, the canonical state space model with d-step delay is transformed into an identification model. The stochastic gradient algorithm is raised to identify the parameter vectors. Finally, an example is presented to validate the given algorithms.
Keywords
delay systems; gradient methods; linear systems; state estimation; state-space methods; stochastic processes; canonical state space model; d-step delay; linear systems; linear transformation; parameter estimation problems; parameter vector identification; shift operator property; state estimation problems; state space system; stochastic gradient algorithm; Computational modeling; Heuristic algorithms; Mathematical model; Signal processing algorithms; Stochastic processes; Vectors; State space models; Stochastic gradient algorithm; Time-delay;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location
Changsha
Print_ISBN
978-1-4799-3707-3
Type
conf
DOI
10.1109/CCDC.2014.6852484
Filename
6852484
Link To Document