In this paper, we investigate the trajectory tracking control problem of surface ships subject to unknown parameters, unknown time-varying disturbances, and input saturation. The input saturation is approximated using a Gaussian error function. The compounded uncertain term caused by the unknown parameters and disturbances is transformed into a linear parametric form with a single parameter called virtual parameter. Then, a novel robust adaptive ship trajectory tracking control law is designed using the adaptive vector-backstepping design method, where the adaptive law online provides the estimation of the virtual parameter. Further, a finite-time control scheme is developed injecting a power function vector of the position and velocity errors into the proposed control scheme such that the control performance is improved. Both our control schemes are simple to compute and easy to implement in engineering applications. Theoretical analysis indicates that the designed control laws can force the surface ship to track the desired trajectory while guaranteeing the global uniform ultimate boundedness of all the signals in the closed-loop trajectory tracking control system of surface ships. Simulation results and comparison verify the effectiveness of our novel robust adaptive trajectory tracking control schemes.

A novel robust adaptive neural network (NN) control scheme with prescribed performance is developed for the 3-D trajectory tracking of underactuated autonomous underwater vehicles (AUVs) with uncertain dynamics and unknown disturbances using new prescribed performance functions, an additional term, the radial basis function (RBF) NN, and the command-filtered backstepping approach. Different from the traditional prescribed performance functions, the new prescribed performance functions are innovatively proposed such that the time desired for the trajectory tracking errors of AUVs to reach and stay within the prescribed error tolerance band can be preset exactly and flexibly. The additional term with the Nussbaum function is designed to deal with the underactuation problem of AUVs. By means of RBF NN, the uncertain item lumped by the uncertain dynamics of AUVs and unknown disturbances is eventually transformed into a linearly parametric form with only a single unknown parameter. The developed control scheme ensures that all signals in the AUV 3-D trajectory tracking closed-loop control system are bounded. Simulation results with comparisons show the validity and the superiority of our developed control scheme.

In this paper, the trajectory tracking problem of underactuated surface vessels (USVs) that is subject to input saturation, unmodeled dynamics, and marine environmental disturbances is investigated. Firstly, USVs underactuation problem is handled by constructing a coordinate transformation. An auxiliary dynamic system is adopted to deal with input saturation. The adaptive law is presented to online update the upper bounds of the composite disturbances. The event-triggering condition is introduced to reduce drastically control execution frequency and the transmission load. By combining the auxiliary dynamic system, an adaptive technique, a first-order command filtered technique and an event-triggered condition, a novel adaptive finite time event-triggered control (AFETC) scheme is proposed, which has the following significant characteristics compared to most existing schemes: 1) the artfully constructed coordinate transformation not only avoids computational complexity but also simplifies the design; 2) the first-order command filtering vector-backstepping control method not only circumvents “explosion of complexity” in the traditional backstepping approach, but also ensures the finite-time settling of position tracking errors of USVs; 3) with the event triggered control, it reduces the control execution frequency, thereby decreasing the communication transmission load; and 4) it ensures stable tracking without requiring a priori information of the unmodelled dynamics of USVs or external disturbances. The designed robust adaptive control has proven to enable USVs to track the desired trajectory while guaranteeing the closed-loop stability in a finite time and avoiding Zeno behavior. Simulation and comparation results demonstrate the effectiveness and superiority of the proposed control strategy.

An adaptive robust control law is proposed for the course tracking problem of ships in this paper incorporating a Nussbaum function and an auxiliary dynamic system into the adaptive dynamic surface control (DSC) technique. The ship steering dynamics is described by the Norrbin nonlinear model with completely unknown control coefficient, parameter uncertainties, and unknown external disturbances and input saturation caused by the rudder constraint. The Nussbaum function is adopted to deal with completely unknown control coefficient and avoid the controller singularity problem. An auxiliary dynamic system is introduced to handle the effect of input saturation. The DSC technique makes the control law be simple to compute and easy to implement in engineering practice. It is proved that the proposed course tracking control law of ships makes the course tracking error be arbitrarily small by an appropriate choice of the design parameters and guarantees the uniform ultimate boundedness of all signals in the closed-loop ship course control system. Finally, simulation results on two ships and simulation comparison with an existing adaptive neural control scheme demonstrate the effectiveness and the superiority of the proposed control scheme.