A synthesis based approach to automated filter tuning

2000 ◽  
Author(s):  
D. Ibbetson
Keyword(s):  
Filter Tuning

scholarly journals Peak Filter Tuning based on Disturbance Spectrum for MIMO High-Precision Scan Stage

2020 ◽  
Vol 53 (2) ◽  
pp. 8413-8418
Author(s):  
Masahiro Mae ◽  
Wataru Ohnishi ◽  
Hiroshi Fujimoto ◽  
Koichi Sakata ◽  
Atsushi Hara
Keyword(s):  
High Precision ◽  
Filter Tuning

scholarly journals Particle Swarm Optimization Based Adaptive Kalman Filters for Fault Diagnosis of Reaction Wheels

2021 ◽  
Author(s):  
Afshin Rahimi
Keyword(s):  
Parameter Estimation ◽  
Kalman Filter ◽  
Fault Diagnosis ◽  
Fault Detection ◽  
Unscented Kalman Filter ◽  
Particle Swarm ◽  
Filter Parameter ◽  
Filter Performance ◽  
Filter Tuning ◽  
Selection Of

There has been an increasing interest in fault diagnosis in recent years, as a result of the growing demand for higher performance, efficiency, reliability and safety in control systems. A faulty sensor or actuator may cause process performance degradation, process shut down, or a fatal accident. Quick fault detection and isolation can help avoid abnormal event progression and minimize the quality and productivity offsets. In space systems specifically, space and power are limited in the satellites, which means that hardware redundancy is not very practical. If actuator faults occur, analytical redundancy techniques should be employed to determine if, where, and how the fault(s) occurred. To do so, different approaches have been developed and studied and one of the wellknown approaches in the literature is using the Kalman Filter as an observer for the purpose of parameter estimation and fault detection. The gains for the filter should be selected and the selection of the process and measurement noise statistics, commonly referred to as “filter tuning,” is a major implementation issue for the Kalman filter. This process can have a significant impact on the filter performance. In practice, Kalman filter tuning is often an ad-hoc process involving a considerable amount of time for trial and error to obtain a filter with desirable –qualitative or quantitative- performance characteristics. This thesis focuses on presenting an algorithm for automation of the selection of the gains using an evolutionary swarm intelligence based optimization algorithm (Particle Swarm) to minimize the residuals of the estimated parameters. The methodology can be applied to any filter or controller but in this thesis, an Adaptive Unscented Kalman Filter parameter estimation applied to a reaction wheel unit is used for the purpose of performance evaluation of the proposed methodology.

Filter tuning system using fuzzy logic

1994 ◽  
Vol 30 (11) ◽  
pp. 846 ◽  
Author(s):  
O. Moreira-Tamayo ◽  
J. Pineda de Gyvez ◽  
E. Sanchez-Sinencio
Keyword(s):  
Fuzzy Logic ◽  
Filter Tuning

scholarly journals Identification of Sudden Stiffness Change in the Acceleration Response of a Nonlinear Hysteretic Structure

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Sheng-Lan Ma ◽  
Shao-Fei Jiang ◽  
Chen Wu ◽  
Si-Yao Wu
Keyword(s):  
Structural Model ◽  
Dynamic Responses ◽  
Physical Parameters ◽  
Discrete Wavelet ◽  
Time Varying ◽  
Ground Acceleration ◽  
Structural Dynamic ◽  
Filter Tuning ◽  
Structural Responses ◽  
Extent Of Damage

The integration of discrete wavelet transform and independent component analysis (DWT-ICA) method can directly identify time-varying changes in linear structures. However, better metrics of structural seismic damage and future performance after an event are related to structural permanent and total plastic deformations. This study proposes a two-stage technique based on DWT-FastICA and improved multiparticle swarm coevolution optimization (IMPSCO) using a baseline nonlinear Bouc–Wen structural model to directly identify changes in stiffness caused by damage as well as plastic or permanent deflections. In the first stage, the measured structural dynamic responses are preprocessed firstly by DWT, and then the Fast ICA is used to extract the feature components that contain the damage information for the purpose of initially locating damage. In the second stage, the structural responses are divided at the identified damage instant into segments that are used to identify the time-varying physical parameters by using the IMPSCO, and the location and extent of damage can accordingly be identified accurately. The efficiency of the proposed method in identifying stiffness changes is assessed under different ground motions using a suite of two different ground acceleration records. Meanwhile, the effect of noise level and damage extent on the proposed method is also analyzed. The results show that in a realistic scenario with fixed filter tuning parameters, the proposed approach identifies stiffness changes within 1.25% of true stiffness within 8.96 s; therefore, it can work in real time. Parameters are identified within 14% of the actual as-modeled value using noisy simulation-derived structural responses. This indicates that, in accordance with different demands, the proposed method can not only locate and quantify damage within a short time with a high precision but also has excellent noise tolerance, robustness, and practicality.

scholarly journals Microwave photonic filter tuning by varying the optical link length

2010 ◽  
Author(s):  
G. Aguayo-Rodriguez ◽  
I. E. Zaldivar-Huerta ◽  
A. Garcia-Juarez ◽  
J. Rodriguez-Asomoza ◽  
L. Larger ◽  
...  
Keyword(s):  
Link Length ◽  
Optical Link ◽  
Microwave Photonic ◽  
Filter Tuning
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