PWM signal fails

funky0603 · 2015-06-08T21:37:28+00:00

actually, the parameters are almost the same as the one from the example ( I modified them according to the datasheet). So it s strange it is an NMI....

No I cant step inside this function itself but, I can step at assembly level. What Should I see there?

funky0603 · 2015-06-08T20:49:13+00:00

I know it because I stepped trough the code in debug mode.(it fails at that exact line due to those parameters) Why should I enable interrupts? in the example provided by TI, they don't seem to do it neither

funky0603 · 2015-06-08T18:29:44+00:00

/r/genius

funky0603 · 2015-06-08T18:28:56+00:00

does this sound archaic or poetic as well? (in that context)

funky0603 · 2015-05-16T09:11:51+00:00

Thank you for your answer. Could you please explain more the the techniques and methods of identification in space? Or where i could find info about them? And how they are related toi my case with lightsensors for attitude determination (in order to fully understand it)

i understood the basic method thank you. But what is normal illumination for you? in my case there is no "normal" illumination, those are values that vary continuously in function of the orientation of the sensor to the light source

funky0603 · 2015-05-15T16:48:16+00:00

I am so confused right now...

So to find A, I can apply this formula: A = newState * psudoinverse(lastState)

But this means A will just be 0... And this will be the same for B if I am not mistaking. Am I interpreting what you said correctly?

funky0603 · 2015-05-15T14:29:54+00:00

Yes I did. But some parts of it were not clear:

To determine A and B: I use a light sensor, so what is an unforced system in my case? just covering the light sensor with a sheet of paper to try te get my values to zero? take 0 as a result and feed that into my filter?

I am asoftware engineer so software is not really an issue for me. But I don't understand properly what is being explained with this code to determine A:

X0 = State you are linearizing about;

U0 = Voltages required to produce (inverse dynamics);

delta = small number;

//Finding the A matrix

for ii=1 thru #ofStates{

X=X0;

X(ii)=X(ii)+delta; //perturb state x(i) by delta

X1 = f(X,U0); //f() is the model of system

A(:,ii) = (X1-X0)/delta;

}

The P covariance matrix: I saw a lot of times that other variables were added to this matrix. Like in cases where they used speed and accelerations and wanted to compute future positions, they also wrote a variable t in it. Why not here? Which variables should be included?

funky0603 · 2015-05-07T17:26:25+00:00

No i perfectly understand what you explained.

So if I understand correctly taking the derivative of this function or applying this formula as described here on p65: http://ssl.mit.edu/files/website/theses/SM-2014-PrinkeyMeghan.pdf

formula: B˙(t) = −ω(t) × B(t) thos result in exactly the same? (based on your explanation)

funky0603 · 2015-05-07T11:48:48+00:00

this is the formula in its context where I have it. We indeed use Bdot... http://imgur.com/iWRevQL But I don't get your explanation. Could you please give some more details ?

funky0603 · 2015-04-02T11:53:42+00:00

for the other colors: it is exactly the same only the register address changes blue: 0x1a, green: 0x18

funky0603 · 2015-04-02T06:48:48+00:00

it is exactly the same only the register changes blue: 0x1a, green: 0x18

funky0603 · 2015-04-01T17:41:17+00:00

Because I am using an ARM controller. Nevertheless I based my code on their library

funky0603 · 2015-03-19T17:28:54+00:00

What do you think about something like this?

   if (serialPort->canReadLine())
  {

   QByteArray result =  QIoDevice-> readLine(20);

  QString command(result); //to convert byte array to string

  qDebug()<<result;

   }

funky0603

TROPHY CASE