Team AVR - Control, Vision and Robotics Lab

Identification benchmark

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A benchmark on the identification of a flexible serial manipulator using a camera for testing MIMO LPV approaches

E. Laroche∗ L. Cuvillon∗ D. Vizer∗∗,∗∗∗ G. Mercère∗∗

∗ ICube lab., University of Strasbourg & CNRS, France. E-mail: laroche,

∗∗ LIAS, University of Poitiers, France. E-mail:

∗∗∗ University of Technology and Economics of Budapest, Department of Control Engineering and Informatics, Magyar Tudo ́sok krt. 1-3 1117, Budapest, Hungary. Email:

This benchmark is dedicated to the identification of a flexible manipulator using a camera. Robotic systems are usually identified using joint-level data (torque and position). However, in the current framework of vision-based control, the model must be able to predict the position of the instrument provided by the camera. Joint positions are also provided as inner variables and can also be used to improve the accuracy of the identified model. One additional complexity source is the presence of flexible modes that need to be accounted for in order to obtain a high bandwidth in control. The proposed simplified case with two inputs and two outputs is considered as sufficient to deal with the non-linear flexible nature of the system. This benchmark is likely to suit for LPV identification methods.

keywords: flexible manipulator; LPV model; system identification; vision-based control

A paper on that benchmark will be presented to the 17th IFAC Symposium on System Identification (SYSID'15, copy sent upon request). Thanks to refer to the paper in your publications.

Download the data (the archive includes the data and the presentation files to be executed with Matlab. To launch the demonstration, execute main.m)

Any request can be sent by email to