Increasing trajectory tracking accuracy of industrial robots using SINDYc

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Bilal, Diyar Khalis and Ünel, Mustafa (2021) Increasing trajectory tracking accuracy of industrial robots using SINDYc. In: 4th IFAC Conference on Embedded Systems, Computational Intelligence and Telematics in Control, CESCIT 2021, Valenciennes, France

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Abstract

In this work a feedforward control approach based on SINDYc (Sparse Identification of Nonlinear Dynamics with Control) is proposed for increasing the trajectory tracking accuracy of industrial robots. Initially, the dynamic relationship between the desired and the actual trajectory is sparsely identified using polynomial basis functions. Then a new trajectory is created from the desired trajectory using a feedforward controller based on the inverse of the sparsely identified dynamic model. The effectiveness of the proposed approach is evaluated by a simulation study in which 4 different KUKA robots were tasked to follow 16 distinct trajectories based on ISO 9283 standard. The obtained results show that the proposed method successfully models the dynamic relationship between the desired and the actual trajectory with accuracies above 98.09% when all of the robots are considered. Moreover, the developed feedforward controller improves the trajectory tracking accuracy of industrial robots by at least 91.1% and 94.5% for position and orientation tracking, respectively while providing parsimonious models.
Item Type: Papers in Conference Proceedings
Uncontrolled Keywords: Industrial Robots, Trajectory Tracking, Feedforward Control, Data Driven Modeling, Sparse Regression
Subjects: T Technology > TJ Mechanical engineering and machinery > TJ163.12 Mechatronics
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Mechatronics
Faculty of Engineering and Natural Sciences > Academic programs > Manufacturing Systems Eng.
Faculty of Engineering and Natural Sciences
Depositing User: Mustafa Ünel
Date Deposited: 26 Aug 2021 19:13
Last Modified: 27 Aug 2022 11:50
URI: https://research.sabanciuniv.edu/id/eprint/41783

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