Abstract

ALANIS, Alma Y.; RIOS, Jorge D.; ARANA-DANIEL, Nancy  and  LOPEZ-FRANCO, Carlos. Real-time neural control of all-terrain tracked robots with unknown dynamics and network communication delays. Ing. invest. y tecnol. [online]. 2020, vol.21, n.3, 00006.  Epub Dec 02, 2020. ISSN 2594-0732.  https://doi.org/10.22201/fi.25940732e.2020.21.3.026.

Currently, wireless communication networks have been acquired great relevance in our daily life, including data acquisition, data processing, control and analysis in different applications. Therefore, robotic systems cannot be an exception, in such a way, it is an important study that considers the effects caused by inclusion of wireless networks in the control loop of robotic systems, as well as, the designing of intelligent control systems that can deal with such effects in real-time. Hence, this research work focuses on the designing of an on-line intelligent controller that achieves trajectory tracking of a robotic mobile system which is in a networked communication environment. The proposed controller can deal with unknown dynamics, unknown external and internal disturbances, unknown communication delays and packet losses. Such a controller is designed using a discrete-time approach based on an inverse optimal control methodology for trajectory tracking and a recurrent high-order neural network identifier. Applicability of the proposed scheme is shown through real-time results using a tracked robot platform controlled through a wireless network under different network scenarios. Besides, obtained results, show good performance. The designed scheme can be extended to any unknown or uncertain nonlinear system which lies in a networked environment. One of the main advantages of the proposed scheme is the robustness of the proposed intelligent controller to work on networked environments under direct communication channels, as well as through two different communication channels, evidently for more complex configurations of the used communication channel, the performance of the proposed scheme can be deteriorated.

Keywords : Neural networks; networked control system; cyber-physical systems; time delay; tracked robot.