Hi all, I've finished to integrate and test my pole placement code, here is the url of the diff. I'd like to know what you think before issuing a pull request. https://github.com/I--P/scipy/compare/pole-placement As said a few days ago there are two algorithms, KNV method 0 (KNV0) and Yang Tits (YT). See code for urls to the reference papers. Motivations for doing this in pure Python rather than linking some old fortran code: I was in need of a 100% Python dependency free (except Numpy of course) pole placement function, integrating it into scipy was not my primary goal. Fortran code used for decades will for sure be faster and bug free but it was not an option. Regarding KNV0: - Licensing issues: I chose this method before knowing Matlab used it too. I did read some old matlab source code (circa 2001 release iirc) at the beginning of my work I won't lie on that, after Ralf Gommers warned me it was not possible to port Matlab code I used my knowledge of their code to stay as far as possible from what they did (the algorithm gives some degrees of freedom). Given the current status of my code I can't see any reason why it would be seen as a rip-off of their code unless I'm banned from coding a projection into a vector space because I read some Matlab code doing it. See lines 1171, 1172 and 1173 in ltisys.py which are the core of this algorithm and are not in any way an idea coming from Mathworks folks, these formulas are clearly written in the reference publication page 1145 and 1146. - Complex poles are not supported by the original algorithm. Using the ideas from the second algorithm below I managed to reach a success rate of 90% with complex poles but this is not reliable enough so the relevant code is disabled. Matlab has a 100% success rate in their 2013 implementation but I don't know how they achieved that (I _*did not*_ check their 2013 code). Regarding Yang Tits algorithm: - This is an update of the KNV0 algorithm published in the mid 90's, as far as I know it is only distributed by Slicot as "contributed MATLAB functions" http://slicot.org/contributed-software under a non-free license. - This implementation is 100% genuine, I did not read the code distributed by slicot past the license header until my code was working so there are no licensing issues imho. After achieving a working implementation of this algorithm I checked the reference implementation from Slicot and I'm still puzzled by how they did it. I'm sure there are tons of good reasons why their implementation is faster/better than mine but I simply can't understand what they did. - Real poles are supported, sometimes the solution has a better conditionning than KNV0's, sometimes not, but it does converge must faster all the time. I was considering adding an option to return the solution with the best conditionning from the two methods but it might confuse users as it would only work on real poles. What do you think ? - Complex poles are supported, I ran it for hours with random matrices and poles and it never failed. Please let me know if this code match you quality standards and I would really be glad if someone could test it and report any bug. The reference matlab implementations of these algorithms have been used and polished for decades, I'm sure I've missed lots of specific cases. As a sidenote, if PR #4249 is accepted it should be possible to greatly improve the speed of these two algorithms.