Re: Moco goals for average speed in cycling model
Posted: Mon Dec 18, 2023 12:41 pm
Hi Ana,
So, in short, the size the control signal can rapidly inflate the control cost, which then might dominate other cost terms (if you have a multi-objective cost function, which you do here with your tracking goal). I usually recommend to keep control signals between [-1, 1] to make cost function term weighting easier. (If all trajectory variables are near [-1, 1] it can also help the optimizer converge, but you can also automate this with scale_variables_using_bounds).
Best,
Nick
The main thing to consider is the effect on the control effort cost. If the control signal is between [-1, 1], then the control cost integrand at a time point is never larger than one. But if the control signal is between [-10, 10], and you're using a squared cost, then the instantaneous cost can be as large as 100. And then those instantaneous costs will be integrated over the trajectory.Is there a practical difference between setting the max force to 10.0 and letting the control signal roam from -1 to 1?
So, in short, the size the control signal can rapidly inflate the control cost, which then might dominate other cost terms (if you have a multi-objective cost function, which you do here with your tracking goal). I usually recommend to keep control signals between [-1, 1] to make cost function term weighting easier. (If all trajectory variables are near [-1, 1] it can also help the optimizer converge, but you can also automate this with scale_variables_using_bounds).
Best,
Nick