I am working on comparing the performance of evolutionary algorithms in optimizing a suspension model. The suspension model is built using ADAMS/Car. I need the best way to implement these algorithms to work in fatest way with our model.
I think you may need some inclusion of filtering techniques for obtaining good accuracy. The best way to use Kalman Filtering, PCA, LDA etc.
Muhammad Ali , thank you for your answer. I am searching for the best way to emplement GA in ADAMS/CAR.
Using ADAMS/CAR along with MATLAB would be a good solution to your problem. You can first define the input and output variables of your model in ADAMS/CAR and then export it to MATLAB Simulink and then try to implement the genetic algorithm on your model in the MATLAB environment. You may find the video in the following link useful. It provides a thorough tutorial on using ADAMS/CAR with MATLAB:
https://youtu.be/2Miky0qNYGE
Matlab and Adams easily coupled to each other. you should just write an appropriate objective function in matlab which can use the date in simulink. then use this function in GA tools. your objective function should go to simulink and run the box of Adams/Car in simulink then Return the response to objective function output.
If you write such an objective function you can use GA tools in matlab and optimize your problem easily.
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