In this paper, we study the trajectory tracking control of underactuated surface vessels(USVs) subject to actuator faults, uncertain dynamics, unknown environmental disturbances, and communication resource constraints. Considering that the actuator is prone to bad faults, the uncertainties formed by the combination of fault factors, dynamic uncertainties and external disturbances are compensated by a single online updated adaptive parameter. In the compensation process, we combine the robust neural-damping technology with the minimum learning parameters (MLPs), which improves the compensation accuracy and reduces the computational complexity of the system. To further improve the steady-state performance and transient response of the system, finite-time control (FTC) theory is introduced into the design of the control scheme. At the same time, we adopt the event-triggered control (ETC) technology, which reduces the action frequency of the controller and effectively saves the remote communication resources of the system. The effectiveness of the proposed control scheme is verified by simulation. Simulation results show that the control scheme has high tracking accuracy and strong anti-interference ability. In addition, it can effectively compensate for the adverse influence of fault factors on the actuator, and save the remote communication resources of the system.

This paper is aiming at enabling the underactuated surface vessels (USVs) to complete the tracking task with high precision and fast convergence under the influence of unknown external interference, dynamic uncertainty, input saturation, limited communication resources, and actuator failure. Specifically, a trajectory tracking control scheme is designed using virtual control switching, robust self-adaptation, finite-time, event-triggered, and disturbance compensation techniques. The norm calculation is performed on the lateral and longitudinal errors of the underactuated USVs, and the virtual guidance direction of the system is obtained through virtual control conversion. The hyperbolic tangent function is introduced and combined with adaptive technology to compensate the dynamic uncertainty of the system. Through the multivariate finite-time disturbance observer (MFTDO), the unknown disturbance and the bias fault factor of the system are compensated. The tracking performance of the system is further improved using the finite-time technology and combined with the event-triggered technology to reduce the update frequency of the controller signal. Using Lyapunov stability theory, a detailed stability analysis is provided for the control scheme. Finally, the effectiveness of the control design scheme is verified by simulation.

This paper deals with the improvement for the tracking performance of underactuated surface vessels (USVs) under input saturation and actuator faults. The neural networks (NNs) are used to reconstruct the dynamic uncertainty of the ship, and an adaptive law is designed to compensate the adverse effects of external unknown disturbances and bias faults on the system. To improve the tracking performance of the system, a nonlinear link is added in the design process of the control scheme to adjust the system error feedback, and the finite-time control (FTC) technology is used to further improve the steady-state performance and transient performance of the system. In addition, to solve the problem of communication resource limitation, an event-triggered mechanism for switching thresholds is introduced, which reduces the update frequency of controller signals. Based on the above techniques, a trajectory tracking control scheme with a performance improvement mechanism is designed. A rigorous stability analysis is provided for the control scheme using Lyapunov stability theory. Finally, the effectiveness of the control scheme is verified by two sets of simulations.

Membrane electrode assemblies (MEAs) are critical components in influencing the electrochemical performance of high-temperature proton exchange membrane fuel cells (HT-PEMFCs). MEA manufacturing processes are mainly divided into the catalyst-coated membrane (CCM) and the catalyst-coated substrate (CCS) methods. For conventional HT-PEMFCs based on phosphoric acid-doped polybenzimidazole (PBI) membranes, the wetting surface and extreme swelling of the PA-doped PBI membranes make the CCM method difficult to apply to the fabrication of MEAs. In this study, by taking advantage of the dry surface and low swelling of a CsH₅(PO₄)₂-doped PBI membrane, an MEA fabricated by the CCM method was compared with an MEA made by the CCS method. Under each temperature condition, the peak power density of the CCM-MEA was higher than that of the CCS-MEA. Furthermore, under humidified gas conditions, an enhancement in the peak power densities was observed for both MEAs, which was attributed to the increase in the conductivity of the electrolyte membrane. The CCM-MEA exhibited a peak power density of 647 mW cm⁻² at 200 °C, which was ~16% higher than that of the CCS-MEA. Electrochemical impedance spectroscopy results showed that the CCM-MEA had lower ohmic resistance, which implied that it had better contact between the membrane and catalyst layer.