Technical Journal, Vol. 13 No. 1, 2019.
Original scientific paper
https://doi.org/10.31803/tg-20180921100632
Investigation on the influence of parameter uncertainties in the position tracking of robot manipulators
Habib Ghanbarpour Asl
; University of Turkish Aeronautical Association, Department of Mechatronics, Bahçekapı Mahallesi, Okul Sk. No: 11, 06790 Etimesgut/Ankara, Turkey
Kerim Youde Han
orcid.org/0000-0001-9073-446X
; Çankaya University, Department of Mechatronics, Yukarıyurtçu Mahallesi Eskişehir Yolu 29. Km, Mimar Sinan Caddesi No: 4, 06790 Etimesgut, Turkey
Abstract
This paper presents a novel trajectory tracking method for robot arms with uncertainties in parameters. The new controller applies the robust output feedback linearization method and is designed so that it is robust to the variation of parameters. Robustness of the algorithm is evaluated when the parameters of the system are floating over 10 percent up and down. An Unscented Kalman Filter (UKF) is applied for state and parameter estimation purposes. As the considered system has 8 unknown parameters while only 5 of them are independent parameters, UKF is applied only to the augmented system with independent parameters. Three types of simulations are applied depending on sensor groups – first with both position and joint sensors, second with only position sensors and third with only joint sensors. The observation of parameters in these groups is discussed. Simulation results show that when both position sensors and joint sensors are used, all the parameters and states are observable and good tracking performances are obtained. When only position sensors are used, the accuracy of the estimated parameters is reduced, and low tracking performances are revealed. Finally, when only joint sensors are applied, the lengths of robot arms are unobservable, but other parameters related to the dynamic system are observable, and poor tracking performances are given.
Keywords
path following; parameter uncertainty; robot control; robust control; sensor fusion; unscented Kalman filter
Hrčak ID:
218157
URI
Publication date:
23.3.2019.
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