We’re using OSQP to solve 4 different MPC problems on vehicle. Before trying OSQP, these problems are solved by CVXGEN.
OSQP converges quickly in two smallest problem and the largest problem (in terms of number of variables and constraints) but couldn’t converge in a reasonable number of iterations (< 2000). CVXGEN however, find the optimum in less than 25 iterations on average.
I wonder if there is any types of QP problem where interior point method is superior to the first order method? We’ve noticed two differences between that problem and the other three:
- it has many more inactive constraints;
- the optimum is not unique.
But we don’t know if it is supported by any theory or there could be anything else. Anything that helps us understand the situation is highly appreciated. Thanks!