discrete simulink model problem

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Meriem dardouri
Meriem dardouri 2018년 1월 9일
댓글: Jim Riggs 2018년 1월 11일
hello everyone, I realized a control program of a single-phase inverter connected to the grid by an LCL filter under matlab / simulink. In the continuos mode, i have got good results (grid current/voltage) , but when I converted the program to the discrete domain every thing went crasy and nothing went right. I can't find what i did wrong. Can anyone help me please?
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Birdman
Birdman 2018년 1월 9일
Can you send your model?
Meriem dardouri
Meriem dardouri 2018년 1월 10일
Sorry, i sent you the wrong model, this is the right one (PVT_1)

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Jim Riggs
Jim Riggs 2018년 1월 10일
Although I am unable to open and view your model, a very common problem when converting from continuous to discrete is that the discrete solver will be based on a forward Euler method. This is much less precise than the higher-order continuous solvers which are commonly used. The first thing that you should try is to run the discrete model with a very small time step - about 100 times or even 1000 times smaller than you were using with the continuous model. See if this helps.
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Meriem dardouri
Meriem dardouri 2018년 1월 11일
Hi Jim, Thanks for your help, i used a time step equal to 0.000001 and it works but when implementing the program on dspace it's not going to work because the time step is too small so do have any other suggestion?
Jim Riggs
Jim Riggs 2018년 1월 11일
You must apply numerical techniques to improve the accuracy of the method. in the attached paper, I show an example of implementing a generic second-order transfer function using a forward-Euler integration method compared to a second-order Runge-Kutta method. You will note that the second-order method results in significantly more complex equations. But you don't need to actually formulate the model in terms of a closed-form equation the way I did in this paper. You can numerically implement the method as described on pages 3 and 4 of the paper. This should give good performance and allow you to reduce the time step by two orders of magnitude.

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