scholarly journals SIMULATION OF AN ADARTIVE FILTER BASED ON THE RECURSIVE LEAST SQUARES METHOD

Author(s):  
О. Sotnik ◽  
S. Marchenko ◽  
О. Hulesha ◽  
О. Syanov

Modern electronics systems are high-speed, compact and require the use of energy-efficient digital electronics devices (DED’s) such as microcontrollers, programmable logic integrated circuits (FPGA’s), digital signal processors. Application of  the  DED’s  is a hardware implementation of high - performance digital signal processing (DSP) algorithms based on the target architecture of the electronic device. In order to accellarate of the design process in the  direct hardware implementation of  DSP algorithms, simulation models are created to enable optimizing the design process at the stage of a creation of the  programming part for FPGA. The paper presents the results of a study of the adaptive filter (AF) model based on the recursive least squares method (RLS). According to the analysis of time and frequency parameters of the AF model has been conducted  during  simulation it was found that the qualitative filtering process starting from the 24th order and further increasing the AF order does not significantly improve signal filtering, but only increases the required hardware resources. In process of the verification of the proposed simulation model, the AF-based noise reduction system has been modeled and the  THD  level of 7.103 % was obtained for the built-in AF unit, which is more than one and a half times higher than the proposed AF unit 4.323 %, which confirmed the efficiency of the developed AF unit. Thus, during the study, the optimal order of AF has been determined, which will allow more efficient use of FPGA resources during the hardware implementation of AF. In accordance with the results of the study, the correctness and efficiency of the created hardware-oriented simulation model has been proved, as well as the hardware-oriented structure of the adaptive RLS filter for future implementation on FPGA nas been shown.

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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