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Filters Design Based On Multiple Characteristic Functions for the Grinding Process Cylindrical Workpieces
- Source :
- IEEE Transactions on Industrial Electronics. 64:4671-4679
- Publication Year :
- 2017
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2017.
-
Abstract
- This paper designs a novel filter based on characteristic function for multidimensional observation systems, essentially extending the proposed filter, which just fitted to one-dimensional observations. For the dynamic model from grinding process cylindrical workpieces, this filter could result in enhanced and incremental productivity and quality control in manufacturing processes. In the processing of the filter design, a new form of filter will be given to adapt to the multidimensional observations, the matrix format of performance index will be designed to fit to matrix format of filter gain, the selecting range of the weighting function vector will be given to ensure the uniform boundedness of the designed performance index, and the filter gain can be obtained by minimizing the performance index. Finally, we illustrate the effectiveness of the proposed method by simulation examples in the field of the target tracking and the grinding process cylindrical workpieces.
- Subjects :
- 0209 industrial biotechnology
Characteristic function (probability theory)
020208 electrical & electronic engineering
02 engineering and technology
Weighting
Adaptive filter
Filter design
Matrix (mathematics)
020901 industrial engineering & automation
Control and Systems Engineering
Filter (video)
Control theory
0202 electrical engineering, electronic engineering, information engineering
Kernel adaptive filter
Uniform boundedness
Electrical and Electronic Engineering
Mathematics
Subjects
Details
- ISSN :
- 15579948 and 02780046
- Volume :
- 64
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Industrial Electronics
- Accession number :
- edsair.doi...........3a812c9de8e57eaa54909e0c2da3133e
- Full Text :
- https://doi.org/10.1109/tie.2017.2668980