Adaptive Dynamic Surface Control Based Cooperative Path Following Of Autonomous Marine Vehicles

In recent years, with the development of marine technology, the way of working for autonomous marine vehicles has been changed from single vehicle to multiple vehicles. Multiple autonomous marine vehicles can perform more difficult tasks that cannot be performed by a single one. Hence, the consistent explores of cooperative path following problem for multiple autonomous marine vehicles are of great significance. This thesis aims to address the control problem for both fully actuated and underactuated autonomous marine vehicles. Nonliner system control theory, graph theory, dynamic surface control technology, neural network adaptive technology, state feedback, output feedback and many other analytic tools are employed. The problem of uncertainties, control algorithm complexities, unmeasurable states, high frequency disturbances and input saturation are considered. The main contributions of this thesis are summarized as follows:First, we considered the cooperative path following problem of autonomous marine vehicles with uncertainties and disturbances. Dynamic surface control technique is employed to the controller design of cooperative path following for both fully actuated autonomous marine vehicles and underactuated autonomous marine vehicles. By online approximating the uncertainties and disturbances, a neural network adaptive cooperative path following control design is developed for autonomous marine vehicles using dynamic surface control technique. Based on the Lyapunov stability analysis, it is proved that all signals of closed-loop systems are semiglobally uniformly ultimately bounded. The effectiveness of control algorithm is verified by numerical simulations.Second, for the problem of cooperative path following of fully actuated autonomous marine vehicles, we concerned with the case of unmeasured velocities caused by technique reason or hazard environment disturbances. By employing the output feedback method, the estimated values of required velocities information are obtained through independent measurement of positions, and then feedback controllers are designed. At the same time, dynamic surface control technique is incorporated into the output feedback controller design. By online approximating the uncertainties and disturbances, an observer based neural adaptive cooperative path following control design is developed. Based on Lyapunov stability analysis, it is proved that the cooperative path following tracking errors converge to a small neighborhood of origin. Simulation studies are performed to demonstrate the effectiveness of the proposed control method.Third, for the problem of cooperative path following of underactuated autonomous marine vehicles, we consider the situation that the system suffered from high frequency disturbances. To overcome this problem, a filtering neural network adptive law is derived. The proposed filtering neural network adptive algorithm has the ability of low frequency learning, which means high frequency part of the disturbances can be filtered and low frequency part of the disturbances can be well learned. The proposed adaptive control algorithm with filtering adaptive laws allow for suppressing the undesired high-frequency oscillations contained in the system response while compensating the uncertainties using standard adaptive algorithm. Based on the Lyapunov stability analysis, it is proved that all signals of closed-loop system are semiglobally uniformly ultimately bounded. The effectiveness of proposed method is shown through simulation results.Fourth, the input saturation problem of autonomous marine vehicles is considered in this thesis. By incorporating the auxiliary system design, an anti-windup control architecture is developed for the cooperative path following design for both fully actuated marine vehicles and underactuated autonomous marine vehicles, and enables good performance of the closed-loop system although the control signals are saturated. At the same time, the amount of communications is reduced effectively due to the distributed speed estimator, which means the global knowledge of the reference speed is relaxed. Under the proposed controllers, all signals in the closed-loop system are guaranteed to be semiglobally uniformly ultimately bounded. Simulation results validate the performance and robustness of the proposed strategy.