scholarly journals The parameters estimation of the linear static objects with use of the recursive least-squares method in the Simulink environment

Author(s):  
Aleksandr Voevoda ◽  
◽  
Galina Troshina ◽  
2005 ◽  
Vol 18 (3) ◽  
pp. 467-478 ◽  
Author(s):  
Radojka Krneta ◽  
Sanja Antic ◽  
Danilo Stojanovic

The procedure of parameters identification of DC motor model using a method of recursive least squares is described in this paper. To identify the system an experimental measuring of signals was carrying out at input - supply of voltage and output of the system for identification - motor angle speed. For the needs of the experiment, a system has been configured with a motor and an optical encoder whose output is connected with the counter input of acquisition card LCK-6013 which over a block connector CB-68LP makes a connection with a computer. The speed of the motor measured by optical encoder is compared with the speed of identified system in order to confirm the quality of the motor model?s parameters estimation.


2021 ◽  
pp. 107754632110191
Author(s):  
Fereidoun Amini ◽  
Elham Aghabarari

An online parameter estimation is important along with the adaptive control, that is, a time-dependent plant. This study uses both online identification and the simple adaptive control algorithm with velocity feedback. The recursive least squares method was used to identify the stiffness and damping parameters of the structure’s stories. Identification was carried out online without initial estimation and only by measuring the structural responses. The limited information regarding sensor measurements, parameter convergence, and the effects of the covariance matrix is examined. The integration of the applied online identification, the appropriate reference model selection in simple adaptive control, and adopting the proportional integral filter was used to limit the structural control response error. Some numerical examples are simulated to verify the ability of the proposed approach. Despite the limited information, the results show that the simultaneous use of online identification with the recursive least squares method and simple adaptive control algorithm improved the overall structural performance.


2012 ◽  
Vol 220-223 ◽  
pp. 1044-1047 ◽  
Author(s):  
Zhao Hua Liu ◽  
Jia Bin Chen ◽  
Yu Liang Mao ◽  
Chun Lei Song

Autoregressive moving average model (ARMA) was usually used for gyro random drift modeling. Because gyro random drift was a non-stationary, weak non-linear and time-variant random signal, model parameters were random and time-variant, too. For improving precision of gyro and reducing effects of random drift, this paper adopted two-stage recursive least squares method for ARMA parameter estimation. This method overcame the shortcomings of the conventional recursive extended least squares (RELS) algorithm. At the same time, the forgetting factor was introduced to adapt the model parameters change. The simulation experimental results showed that this method is effective.


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