Induction Motor Parameter Identification Using Gravitational Search Algorithm
The files allow the identification of induction motors through the use of the Gravitational Search Algorithm (GSA)
In this application we used the Gravitational search algorithm to determinate the internal parameters of an induction motor. The GSA is an algorithm inspired in laws of gravity that emulates masses which attract each other, where each mass is a candidate solution.
For the Induction motor parameter identification, the algorithm is initialized with the variables that the application requires. In this case were used three parameters R1, R2 and X1.
R1 = L(1);
R2 = L(2);
X1 = L(3);
To execute the algorithm we have to indicate the number of agents (N), maximum number of iterations (max_it), Elitist check (Elitistcheck), minimization or maximization (min_flag) and power R (Rpower).
The algorithm displays best fitness (Fbest), best solution (Lbest), best fitness in each iteration (BestChart) and mean of BestChart (meanChart).
To run the algorithm we suggest the following configuration:
[Fbest,Lbest,BestChart,MeanChart]=GSA(25,3000,1,1,1);
For further information visit:
http://www.mdpi.com/2073-431X/5/2/6
The code can be used without restriction, please cite us
Avalos, O.; Cuevas, E.; Gálvez, J. Induction Motor Parameter Identification Using a Gravitational Search Algorithm. Computers 2016, 5, 6.
Cite As
Erik (2024). Induction Motor Parameter Identification Using Gravitational Search Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/56813-induction-motor-parameter-identification-using-gravitational-search-algorithm), MATLAB Central File Exchange. Retrieved .
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Version | Published | Release Notes | |
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1.0.0.0 | The description was updated The description was updated |