A Methodology for Simply Evaluating the Safety of a Passenger Ship Stability Using the Index for the Intact Stability Appraisal Module.

To evaluate the safety of passenger ships' stability, ten stability parameters should be calculated. However, since the process for calculating all stability parameters is complex without a ship loading program, a convenient methodology to simply calculate them and evaluate the safety condition of a passenger ship is required to alert the hazard to a captain, officer, and crew. The Index for Passenger Ship Intact Stability Appraisal Module (IPSAM) is proposed herein. According to the value of a passenger ship's metacentric height (GM) which could be calculated by the ship's roll period measured by sensors in real-time, IPSAM simply calculates nine intact stability parameters except for AnglemaxGZ and proposes the present stability status as a Single Intact Stability Index (SISI). It helps crews easily recognize the safety of passenger ships' stability as a decision support system in real-time. Based on the intact stability parameters of 331 loading conditions of 11 passenger ships, empirical formulas for IPSAM were derived. To verify the empirical formulas of IPSAM, the stability parameters of a passenger ship in 20 loading conditions were calculated using proposed empirical formulas and the principal calculation methods respectively, then compared. Additionally, the result of the SISI of 20 loading conditions successfully indicates the danger as the value of the SISI under 1.0 of the three loading conditions that do not satisfy the IMO intact stability requirements.

Adaptive fuzzy tracking control for underactuated surface vessels with unmodeled dynamics and input saturation.

This paper investigates the tracking control of the underactuated surface vessel (USV) with the off-diagonal inertial matrix, and under the influence of unmodeled dynamics as well as the constraint of input saturation. With the fuzzy logic systems (FLSs) accounting for the uncertainties, we present an adaptive fuzzy state-feedback control scheme with the minimum learning parameters (MLPs) of the FLSs. Based on the conventional USV model described in three degrees of freedom (DOF), an improved model is established at first, which involves the terms of dynamic disturbances generated by the unmodeled dynamics of the indecisive motions. Then, the off-diagonal inertial matrix is released by restructuring the kinematic loop of the improved model, and the backstepping approach is employed through the control design. To solve the underactuated problem, the tracking error in the sway motion is restructured by adding an adaptive compensating variable and further allocated to the actuated motions. The K∞ functions are structured in the control laws to offset the dynamic disturbances. The Gauss error functions are employed to approximate the uncertainties of the input saturation, which are described by the continuous control inputs with the bounded multiplicative gains. Via the small-gain theorem, the resulting closed-loop system is proved to be ultimately bounded. Finally, a simulation example is carried out to validate the effectiveness of the developed scheme.

Model-Based Event-Triggered Tracking Control of Underactuated Surface Vessels With Minimum Learning Parameters.

This article studies the model-based event-triggered control (ETC) for the tracking activity of the underactuated surface vessel (USV). Following this ideology, the continuous acquisition of states is no longer needed, and the communication traffic is reduced in the channel of sensor to controller. The control laws are fabricated in the frame of an adaptive model, which is renewed with the states of the original system whenever the triggering condition is violated. In the scheme, both internal and external uncertainties are approximated by the neural networks (NNs). To decrease the computing complexity, the minimum learning parameters (MLPs) are involved both in the adaptive model and the derived controller. The adaptive laws of only two MLPs are devised, and their updating only happens at triggering instants. Using the MLPs, an adaptive triggering condition is further derived. To avoid the "Zeno" phenomenon in small tracking errors, a dead-zone operator is designed for the triggering condition. Furthermore, we incorporate the dynamic surface control (DSC) into the controller design, such that the jumping of virtual control laws at triggering instants is smoothed and the problem of "complexity explosion" is circumvented. Through the techniques of the impulsive dynamic system and the direct Lyapunov function, the parameter setting for the DSC is derived to guarantee the semiglobal uniformly ultimate boundedness (SGUUB) of all the error signals in the closed-loop system. Finally, the effectiveness of the proposed scheme is validated through the simulation.