Title :
Partially Coupled Stochastic Gradient Identification Methods for Non-Uniformly Sampled Systems
Author :
Ding, Feng ; Liu, Guangjun ; Liu, Xiaoping Peter
Author_Institution :
Key Lab. of Adv. Process Control for Light Ind. (Minist. of Educ.), Jiangnan Univ., Wuxi, China
Abstract :
This technical note addresses identification problems of non-uniformly sampled systems. For the input-output representation of non-uniform discrete-time systems, a partially coupled stochastic gradient (C-SG) algorithm is proposed to estimate the model parameters with high computational efficiency compared with the standard stochastic gradient (SG) algorithm. The analysis indicates that the partially C-SG algorithm can give more accurate parameter estimates than the SG algorithm. The parameter estimates obtained using the partially C-SG algorithm converge to their true values as the data length approaches infinity.
Keywords :
discrete time systems; gradient methods; parameter estimation; sampled data systems; stochastic systems; nonuniform discrete-time system; nonuniformly sampled system; parameter estimation; partially coupled stochastic gradient identification; Chemical sensors; Computational efficiency; Control systems; Parameter estimation; Predictive control; Process control; Sampling methods; Sensor systems; State estimation; State-space methods; Stochastic systems; Discretization; multirate systems; non-uniform sampling; parameter estimation; recursive identification; stochastic gradient;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2010.2050713
