Mean-Squared Error Analysis of Adaptive Subband-Based System Identification

2008 ◽  
Vol 16 (8) ◽  
pp. 1452-1465 ◽  
Author(s):  
J.H. Gunther ◽  
G. Wilson
Keyword(s):  
System Identification ◽  
Error Analysis ◽  
Mean Squared Error ◽  
Squared Error

scholarly journals Modelling of Horizontal Flexible Plate Structure Using Artificial Bee Colony Algorithm

2018 ◽  
Vol 7 (4.36) ◽  
pp. 415
Author(s):  
Muhamad Sukri Hadi ◽  
Sukri Hadi Zaurah Mat Darus
Keyword(s):  
System Identification ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Mean Squared Error ◽  
Least Square ◽  
Flexible Plate ◽  
Plate Structure ◽  
Bee Colony ◽  
Squared Error ◽  
Plate System

This paper presents the performance of system identification for modeling the horizontal flexible plate system using artificial bee colony and recursive least square algorithms. Initially, the experimental rig of flexible plate was designed and fabricated with all edges clamped boundary condition at the horizontal position. Then, the instrumentation and data acquisition systems were integrated into the rig for acquiring the input-output vibration experimentally. The collected data in the experiment will be used later for modeling the dynamic system of horizontal flexible plate system using system identification. The effectiveness of the developed model will be validated using mean squared error, one step ahead prediction, correlation tests and pole zero diagram stability. The estimated of the developed models were found are acceptable and possible to be used as a platform of controller development for vibration suppression of the undesirable vibration in the flexible plate structure. It was found that the artificial bee colony algorithm has performed better in this study by achieving the lowest mean squared error, good correlation test and high stability in the pole zero diagram.  

Modeling the Vibrational Dynamics of Piezoelectric Actuator by System Identification Technique

2017 ◽  
Vol 7 (3) ◽  
pp. 1506
Author(s):  
Nurul Bahiah Mohd Noor ◽  
Mohd Ridzuan Ahmad
Keyword(s):  
System Identification ◽  
Smart Materials ◽  
Mean Squared Error ◽  
Electrical Signal ◽  
Experimental Result ◽  
Nonlinear Creep ◽  
Squared Error ◽  
Final Prediction Error ◽  
Identification Technique ◽  
Active Vibration

Actuators based on smart materials such as piezoelectric actuators (PEAs) are widely used in many applications to transform electrical signal to mechanical signal and vice versa. However, the major drawbacks for these smart actuators are hysteresis nonlinear, creep and residual vibration. In this paper, PEAs are used for active vibration application. Therefore, a model of PEA must be established to control the vibration that occurs in the system. The frequencies of 1 Hz, 20 Hz and 50 Hz were tested on the PEAs. The results obtained from the experimental were used to develop transfer function model by employing system identification technique. Meanwhile, the model validation was based on level of models fitness to estimation data, mean squared error (MSE), final prediction error (FPE) and correlation test. The experimental result showed that the displacement of the actuator is inversely proportional to the frequency. The following consequences caused the time response criteria at 50 Hz achieved smallest overshoot and fastest response of rise time and settling time.

scholarly journals Mean Squared Error Analysis of Quantizers With Error Feedback

2017 ◽  
Vol 65 (22) ◽  
pp. 5970-5981 ◽  
Author(s):  
Shuichi Ohno ◽  
Teruyuki Shiraki ◽  
M. Rizwan Tariq ◽  
Masaaki Nagahara
Keyword(s):  
Error Analysis ◽  
Mean Squared Error ◽  
Error Feedback ◽  
Squared Error
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