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different state size

Posted: Fri Jan 29, 2016 9:14 am
by bjdekruif
Hello all,

I am using, similar to the DynamicWalkingStarter, Matlab to do the integration of my OS model. However, I use time delayed signals in the simulation, which means that I get a vector with delayed states and I need to known which state is in what index. In the tread (https://simtk.org/forums/viewtopic.php? ... mes#p12925) there is already the warning that the sequence of the state that you get with 'state.getY()' can be different from the sequence you get with 'model.getStateVariable()'. I think I can work around this for the time being.

However, an issue I cannot understand, is that they seem to have different number of states:

Code: Select all

osimModel = Model('underArm_bounce.osim');
osimModel.buildSystem();
st = osimModel.initializeState();
st.getNY
nrS = osimModel.getStateVariableNames().size()
The result is that st indicates 27 states, and nrS returns 26. Does anybody know what this extra state is, and where I might find additional information?

---- update ---
I found that the state in simbody uses the quaternions, which give me the extra state. In simbody's user guide it is stated that you can use Euler angles by setting setUseEulerAngles() on the SimbodyMatterSubsystem. Can this be done from Matlab?


Thanks in advance
Bas

Re: different state size

Posted: Fri Mar 18, 2016 5:38 am
by kohli
Short-term wind speed prediction is very useful for efficient utilization of wind power. Mycielski algorithm is a novel and effective approach alternative to statistical or artificial intelligence based models for wind speed prediction. In order to apply the Mycielski algorithm, the wind speed values are converted to wind states. This paper investigates the effect of different wind speed state sizes on the Mycielski approach for wind speed prediction. The data sets from three different wind farms are used to test the variation of different state sizes for the Mycielski approach. The comparison results and F-test statistics show that the moderate small state size has a significant benefit to predict the wind speed accurately.