In this paper, a neuroadaptive distributed output feedback formation tracking control scheme for multiple marine surface vessels with model uncertainties, unknown environmental disturbances and input and output constraints is proposed. A neural network based observer is developed to reconstruct the unmeasured velocity and approach the model uncertainties. To handle the input constraint, an auxiliary dynamic system is introduced. The tracking error transformation and the barrier Lyapunov function are used to tackle with the output constraint. Subsequently, by using the estimated velocity of neighboring vessels, neuroadaptive distributed output feedback controllers are developed. Furthermore, to avoid directly taking the time derivation of virtual control law and generate smooth reference signals, linear tracking differentiators are employed. Finally, it is shown that all the signals in the closed-loop system are bounded via Lyapunov analysis. Simulations are carried out to verify the proposed control scheme. INDEX TERMS Barrier Lyapunov function, distributed control, input constraint, marine surface vessels, output constraint, output feedback control.
This paper investigates the formation tracking control problem of a group of underactuated surface vessels (USVs) in the presence of model uncertainties and environmental disturbances. Additional constraints, such as collision avoidance, heterogeneous limited communication range and input saturation are also considered. A modified barrier Lyapunov function (BLF) is introduced to achieve the connectivity preservation, the collision avoidance and the distributed formation tracking. Extended state observer (ESO) is employed to estimate total disturbances consisting of environmental disturbances and model uncertainties. Auxiliary variables are introduced to deal with the underactuated problem and input saturation. A distributed controller is developed for each USV. Using the Lyapunov method analyze the stability of the system, it is proven that all signals are bounded and tracking errors converge to a neighborhood of the origin. Simulation results show that the proposed controller is practicable and effective.
This paper investigates a formation tracking problem of underactuated surface vessels (USVs) with collision avoidance and input saturation. All nonlinearities induced by model uncertainties and disturbances are assumed to be unknown. A design of observer based on neural network is used to recover the velocity data and unknown uncertainties and disturbances. Distributed control laws are designed based on artificial potential functions (APFs), the observer, and a backstepping technique. The APFs combined with a practical category are used to avoid collision. Additional controllers are employed to deal with the input saturation and underactuated problems without affecting the capability of collision avoidance. The stability of formation control system is proved by using the Lyapunov's direct method. Simulation results are performed to illustrate the effectiveness of the proposed strategy.
This paper considers the problem of autopilot design for surface ship with environmental disturbances and input saturation. Extended state observer (ESO) is used to reconstruct yaw rate and estimate unknown environmental disturbances. An auxiliary dynamic system is employed to handle the input saturation. By combining with the auxiliary dynamic system and ESO, an event-triggered controller (ETC) is designed, and energy is saved by reduction in the rudder rate. Simulation results illustrate the effectiveness and feasibility of the event-triggered proposed controller.
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