Evolutionary Optimization on Continuous Dynamic Constrained Problems - An Analysis

Author(s):  
Trung Thanh Nguyen ◽  
Xin Yao
1997 ◽  
Vol 36 (04/05) ◽  
pp. 356-359 ◽  
Author(s):  
M. Sekine ◽  
M. Ogawa ◽  
T. Togawa ◽  
Y. Fukui ◽  
T. Tamura

Abstract:In this study we have attempted to classify the acceleration signal, while walking both at horizontal level, and upstairs and downstairs, using wavelet analysis. The acceleration signal close to the body’s center of gravity was measured while the subjects walked in a corridor and up and down a stairway. The data for four steps were analyzed and the Daubecies 3 wavelet transform was applied to the sequential data. The variables to be discriminated were the waveforms related to levels -4 and -5. The sum of the square values at each step was compared at levels -4 and -5. Downstairs walking could be discriminated from other types of walking, showing the largest value for level -5. Walking at horizontal level was compared with upstairs walking for level -4. It was possible to discriminate the continuous dynamic responses to walking by the wavelet transform.


Author(s):  
I. N. Belezyakov ◽  
K. G. Arakancev

At present time there is a need to develop a methodology for electric motors design which will ensure the optimality of their geometrical parameters according to one or a set of criterias. With the growth of computer calculating power it becomes possible to develop methods based on numerical methods for electric machines computing. The article describes method of a singlecriterion evolutionary optimization of synchronous electric machines with permanent magnets taking into account the given restrictions on the overall dimensions and characteristics of structural materials. The described approach is based on applying of a genetic algorithm for carrying out evolutionary optimization of geometric parameters of a given configuration of electric motor. Optimization criteria may be different, but in automatic control systems high requirements are imposed to electromagnetic torque electric machine produces. During genetic algorithm work it optimizes given geometric parameters of the electric motor according to the criterion of its torque value, which is being calculated using finite element method.


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