Find balanced realisation of DLTI system.
Lyapunov equations are solved using iterative squared Smith algorithm, in its low or full rank version. These implementations are as per the low_rank_smith and smith_iter functions respectively but, for computational efficiency, the iterations are rewritten here so as to solve for the observability and controllability Gramians contemporary.
This algorithm is not ideal to exploit sparsity. However, the following strategies are implemented:
if the A matrix is provided in sparse format, the powers of A will be calculated exploiting sparsity UNTIL the number of non-zero elements is below 15% the size of A. Upon this threshold, the cost of the matrix multiplication rises dramatically, and A is hence converted to a dense numpy array.
The settings that this solver accepts are given by a dictionary, with the following key-value pairs:
Use low rank methods