Static Optimization with new Muscle Model
Posted: Fri Sep 03, 2021 9:18 am
Hello OpenSim Team,
we developed a new muscle model where the activation is not a State variable anymore but depending on the normalized Calcium concentration.
After finishing this model, we tested it with some forward simulation. (Just simple excitation of the muscle) This forward simulation worked all fine. Then we tried some inverse simulation, here the inverse kinematics and the inverse dynamics work fine but if we start a static optimization, the solver just "hangs". It neither finds a solution nor the maximum iterations are reached, it just does nothing.
We tested the same setup with the Millard muscle model, which worked fine.
Now we are wondering where is the difference between the muscle models and which methods/state variables do new muscle models need to be used for static optimization?
Many thanks in advance.
Best
Mike
we developed a new muscle model where the activation is not a State variable anymore but depending on the normalized Calcium concentration.
After finishing this model, we tested it with some forward simulation. (Just simple excitation of the muscle) This forward simulation worked all fine. Then we tried some inverse simulation, here the inverse kinematics and the inverse dynamics work fine but if we start a static optimization, the solver just "hangs". It neither finds a solution nor the maximum iterations are reached, it just does nothing.
We tested the same setup with the Millard muscle model, which worked fine.
Now we are wondering where is the difference between the muscle models and which methods/state variables do new muscle models need to be used for static optimization?
Many thanks in advance.
Best
Mike