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Communication Dans Un Congrès IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM) Année : 2013

New Iterative Learning identification and Model Based Control of Robots Using Only Actual Motor Torque Data

Résumé

This paper deals with a new iterative learning dynamic identification method of robot controlled with a Computed Torque Control (CTC) law. The parameters of the Inverse Dynamic Model (IDM), which calculates the CTC, are calculated to minimize the quadratic error between the actual joint force/torque and a joint force/torque calculated with the Inverse Dynamic Identification Model (IDIM), linear in relation to the parameters. Usually the parameters are estimated off-line and the IDIM is calculated with the joint position and the noisy derivative of it and cannot take into account variations of the parameters (IDIM-LS method). The new method called IDIM-ILIC (IDIM with Iterative Learning Identification and Control) overcomes these 2 drawbacks. The parameters are periodically calculated over a moving time window to update the IDM of the CTC, and the IDIM is calculated with the noise-free data of the trajectory generator, which avoids using the noisy derivatives of the actual joint position. An experimental setup on a prismatic joint validates the procedure with stationary parameters and with a variation of the payload.

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Dates et versions

hal-00877574 , version 1 (28-10-2013)

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Maxime Gautier, Anthony Jubien, Alexandre Janot. New Iterative Learning identification and Model Based Control of Robots Using Only Actual Motor Torque Data. IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Jul 2013, Wollongong, Australia. pp.1436-1441, ⟨10.1109/AIM.2013.6584296⟩. ⟨hal-00877574⟩
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