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Download the SMART library

License agreement, disclaimer

  • You are free to use any of the files of the SMART library of the SMAC toolbox for personal or academic use. The express permission of the authors is required for any commercial use.
  • You can redistribute the SMART library of the SMAC toolbox and its manual without modification provided that it is for a non commercial purpose. Redistribution in any commercial form including CD-ROM or any other media is hereby forbidden, unless with the express written permission of the authors. Any of your software developments related to this download will be available under similar license conditions.
  • Neither the authors nor ONERA accept any responsibility or liability with regard to this software that is licensed on an "as is" basis. There will be no duty on authors or ONERA to correct any errors or defects in the software.


Current version of the SMART library: v1.7 released on 6 July 2021.
Older versions:

  • v1.6 released on 12 October 2020
  • v1.5 released on 4 October 2018
  • v1.4 released on 11 July 2016
  • v1.3 released on 12 November 2014
  • v1.2 released on 18 June 2014
  • v1.1 released on 30 April 2014
  • v1.0 released on 21 March 2013

Download and install

  1. Download the SMART library of the SMAC toolbox.
  2. Unzip it in a folder of your choice.
  3. Add this folder to the Matlab path.
  4. Enjoy, and do not hesitate to contact Clément Roos ( in case of trouble or success!


The SMART library of the SMAC toolbox must be referenced when used in any published work:

[1] C. Roos, "Systems Modeling, Analysis and Control (SMAC) Toolbox: an insight into the robustness analysis library", in Proceedings of the IEEE Multiconference on Systems and Control, Hyderabad, India, August 2013, pp. 176-181.

Additional references can also be used. Reference 2 describes the algorithms which are implemented in the library, whereas reference 3 presents some numerical results obtained when applying the library to challenging real-world benchmarks.

[2] C. Roos, F. Lescher, J-M. Biannic, C. Doll and G. Ferreres, "A set of $\mu$-analysis based tools to evaluate the robustness properties of high-dimensional uncertain systems", in Proceedings of the IEEE Multiconference on Systems and Control, Denver, Colorado, September 2011, pp. 644-649.
[3] C. Roos and J-M. Biannic, "A detailed comparative analysis of all practical algorithms to compute lower bounds on the structured singular value", Control Engineering Practice, 44:219-230, 2015.