Event-Sampled Adaptive Fuzzy Control of MASS via Intermittent Position Data

In this article, a novel event-sampled adaptive fuzzy control solution is developed for the tracking issue of maritime autonomous surface ships (MASS) under a cyber environment. In the control design, the network resources constraint, internal/external uncertainties and input saturations are involved. To save the issue of network resources, only the intermittent position data is transmitted for the control design of MASS, and an event-sampled adaptive fuzzy state observer (ESAFSO) that only depends on the intermittent position data is designed to recover the untransmitted velocity. The designed ESAFSO is independent of the design of control law, which can coordinate the network resource-saving and uncertainty compensation. In addition, to accommodate the effect resulting from the event sample, which makes the signal discontinuous required by control design, a new design method is developed by using the backstepping design framework with a multivariable dynamic surface control technique. Furthermore, a dynamic event triggering mechanism is established in the controller-actuator (C-A) channel, and a novel adaptive fuzzy output feedback control solution is developed. Under Lyapunov theory, it is indicated that, under the proposed event-sampled adaptive fuzzy control solution for the MASS only intermittent position data, all signals of the closed-loop control system are proved to be bounded. The effectiveness of the developed control solution is illustrated by simulations.