Real-time neural control of all-terrain tracked robots with unknown dynamics andnetwork communication delays

This work focuses on the design of an intelligent controller that is a considerably large challenge for cyber-physical systems. The proposed controller can deal with unknown dynamics, actuator saturation, unknown external and internal disturbances, unknown communication delays and packet losses. Such a controller is designed using a discrete-time approach based on inverse optimal control and a recurrent high-order neural network identifier. The 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.