Intelligent event-based output feedback control with Q-learning for unmanned marine vehicle systems. (December 2020) - Zhang, Dan; Ye, ZeHua; Chen, PengCheng; Wang, Qing-Guo
Abstract: This paper addresses the Dynamic Output Feedback Control (DOFC) problem for the network-based unmanned marine vehicle (UMV) systems, where the controller is located at the land-based console. The output measurements on the system are transmitted to the land-based console via a communication network. A novel event-based transmission mechanism is devised to alleviate the communication burden, where the threshold of the event function is intelligently updated by a Q-learning algorithm. Since the communication delay is inevitably present in the networked controller design, a time-delay system model is established which incorporates both event-based transmission and communication delay. With help of the Lyapunov stability theory and the extended reciprocally convex matrix inequality approach, a sufficient condition is obtained which ensures asymptotic stability of the tracking error system while a prescribed H ∞ disturbance attenuation performance is met. Finally, the simulation study on a benchmark system shows that the proposed controller design not only attenuates the Yaw Velocity (YV) error variation and the Yaw Angle (YA) oscillation, but also reduces the communication load effectively. Compared with the existing results in literature, it is shown that the proposed control algorithm can provide a better tracking performance.