Title :
Partially coupled estimation algorithm for discrete-time multiple-input multiple-output systems
Author :
Liu, Yanjun ; Ding, Rui
Author_Institution :
Key Lab. of Adv. Process Control for Light Ind. (Minist. of Educ.), Jiangnan Univ., Wuxi, China
Abstract :
In this paper, a partially coupled recursive least squares (PC-RLS) algorithm is proposed to estimate the parameters of a class of multivariable systems. The first step is to decompose the identification model into submodels or subsystems, resulting in the subsystem least squares (S-RLS) algorithm. For the same parameters contained in each submodel, the PC-RLS algorithm is to couple the estimation of the common parameters of each submodel one by one, while the estimates of the common parameters are mutually independent for the S-RLS algorithm. The analysis shows that the PC-RLS algorithm requires less computational burden than the standard recursive least squares method and the S-RLS method. The simulation tests verify the effectiveness of the proposed algorithm.
Keywords :
MIMO systems; discrete time systems; least squares approximations; multivariable control systems; recursive estimation; MIMO systems; PC-RLS algorithm; S-RLS algorithm; discrete time multiple-input multiple-output systems; identification model; multivariable systems; partially coupled estimation algorithm; partially coupled recursive least squares algorithm; subsystem least squares algorithm; Algorithm design and analysis; Covariance matrix; MIMO; Mathematical model; Signal processing algorithms; Stochastic processes; Vectors; Recursive identification; least squares; multivariable systems; partially coupled parameter estimation;
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244335
