Control Algorithms for Robot Manipulator

Abstract:

The subject of this work is to develop a control system for the two degree of freedom robot manipulator. Manipulators play an increasingly important role not only in flexible automation production systems but also in medicine and rehabilitation process [3]. High-speed and high-precision trajectory tracking are indispensable capabilities for versatile applications of manipulators. Even in well-known industrial applications manipulators are characterized by structural and / or unstructured uncertainty. Through structural uncertainty we miss a situation in which we have a dynamic model of the object, but because of the uncertainty unknown parameters such as load, inaccuracies in constant torque actuators etc. to create a properly working control system is a difficult issue. In contrast, unstructured uncertainty is related to the unknown of the dynamic model, which may be due to many reasons such as the presence of high-frequency modes of the manipulator, neglected time-delays, nonlinear friction etc. In this case, when the dynamic model of the system is not known a priori (or not available), the system must first be identified, then the control law is developed based on the estimated model [5, [6[7].These problems cause that it is very difficult to find good control system but simple. In this case, the different algorithms for control system of the manipulator was proposed. The first classical PD controller was tested. Next the system design for PD controller with compensation of gravitational forces.

• Periodical: Applied Mechanics and Materials (Volume 759)
• Pages: 45-50
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.759.45
• Online since: May 2015
• Authors: Agata Nawrocka*, Andrzej Kot, Marcin Nawrocki
• Keywords: Control Algorithms, Mathematical Model, Nonlinear Object, Robot Manipulator, Simulation Tests

References

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[2] M. W Spong, Vidyasagar.: Warszawa, WNT, (1997).

[3] A. Nawrocka, M. Nawrocki, A. Kot: Fuzzy logic controller for rehabilitation robot manipulator, International Carpathian Control Conference (ICCC), Velke Karlovice, Czech Republic, May 28–30, s. 379 – 382, 2014, IEEE Explore.

DOI: 10.1109/carpathiancc.2014.6843631

[4] M. Nawrocki, A. Nawrocka: Artificial neural networks for identification in real time of the robot manipulator model parameters. International Carpathian Control Conference (ICCC), Velke Karlovice, Czech Republic, May 28–30, s. 383 – 386, 2014, IEEE Explore.

DOI: 10.1109/carpathiancc.2014.6843632

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[6] L. Cedro: Identification of an electrically driven manipulator using the differential filters – input error method, Acta Mechanica et Automatica, vol. 6 no. 2 (2012) str. 23-27, Oficyna Wydawnicza Politechniki Białostockiej, ISSN: 1898-4088.

[7] L. Cedro, D. Janecki: Determining of Signal Derivatives in Identification Problems -FIR Differential Filters, Acta Montanistica Slovaca, R 16 (2011), cz. 1, str. 47-54, ISSN 1335-1788.