Underwater vehicles (UVs) are subjected to various environmental disturbances due to ocean currents, propulsion systems, and un-modeled disturbances. In practice, it is very challenging to design a control system to maintain UVs stayed at the desired static position permanently under these conditions. Therefore, in this study, a nonlinear dynamics and robust positioning control of the over-actuated autonomous underwater vehicle (AUV) under the effects of ocean current and model uncertainties are presented. First, a motion equation of the over-actuated AUV under the effects of ocean current disturbances is established, and a trajectory generation of the over-actuated AUV heading angle is constructed based on the line of sight (LOS) algorithm. Second, a dynamic positioning (DP) control system based on motion control and an allocation control is proposed. For this, motion control of the over-actuated AUV based on the dynamic sliding mode control (DSMC) theory is adopted to improve the system robustness under the effects of the ocean current and model uncertainties. In addition, the stability of the system is proved based on Lyapunov criteria. Then, using the generalized forces generated from the motion control module, two different methods for optimal allocation control module: the least square (LS) method and quadratic programming (QP) method are developed to distribute a proper thrust to each thruster of the over-actuated AUV. Simulation studies are conducted to examine the effectiveness and robustness of the proposed DP controller. The results show that the proposed DP controller using the QP algorithm provides higher stability with smaller steady-state error and stronger robustness.

Nowadays, underwater vehicles (UVs) are applied to various tasks such as carrying objects or maintenance of underwater structures. To carry out well these tasks, UVs should keep the position and orientation in the water to perform the specified tasks. However, the systems used in underwater operations are always under the influence of disturbance such as ocean currents and model uncertainties. In this paper, the robust station-keeping (SK) control algorithm based on a sliding mode control (SMC) theory is designed to guarantee stability and better performance of a hovering over-actuated autonomous underwater vehicle (HAUV) despite the existence of model uncertainties and ocean current disturbance in the horizontal plane (HP). Using the Lyapunov theorem, the stability of the proposed controller is demonstrated. Besides, an optimal allocation control (AC) algorithm is also designed to keep the linear position and Euler angles of the HAUV in the presence of model uncertainties as well as ocean currents and to minimize the energy consumption of the system. Finally, a series of simulations and experiments for the HAUV system is conducted to demonstrate the superior performance of the proposed method.

This paper focuses on motion analysis of a coupled unmanned surface vehicle (USV)–umbilical cable (UC)–unmanned underwater vehicle (UUV) system to investigate the interaction behavior between the vehicles and the UC in the ocean environment. For this, a new dynamic modeling method for investigating a multi-body dynamics system of this coupling system is employed. Firstly, the structure and hardware composition of the proposed system are presented. The USV and UUV are modeled as rigid-body vehicles, and the flexible UC is discretized using the catenary equation. In order to solve the nonlinear coupled dynamics of the vehicles and flexible UC, the fourth-order Runge–Kutta numerical method is implemented. In modeling the flexible UC dynamics, the shooting method is applied to solve a two-point boundary value problem of the catenary equation. The interaction between the UC and the USV–UUV system is investigated through numerical simulations in the time domain. Through the computer simulation, the behavior of the coupled USV–UC–UUV system is analyzed for three situations which can occur. In particular, variation of the UC forces and moments at the tow points and the configuration of the UC in the water are investigated.

This paper proposes an adaptive barrier fast terminal sliding mode control (ABFTSMC) approach for quadrotor unmanned aerial vehicles (UAV). Its main objectives are to mitigate the external disturbances, parametric uncertainties, and actuator faults. An adaptive barrier function is considered in the design to ensure the finite-time convergence of the output variables to a predefined locality of zero, independent of the disturbance bounds. A fast terminal sliding mode control (FTSMC) approach is designed to speed up the convergence rate in both reaching and sliding phases. The design considers hyperbolic tangent functions in the adaptive control law to drastically reduce the chattering effect, typically associated with the standard SMC. The performance of the proposed approach was assessed using a quadrotor UAV subject to external disturbances and sudden actuator faults. The obtained results show that the trajectory and the sliding surface converge to the origin in a finite time, without being affected by the high disturbance and actuator faults. In this method, due to the substitution of the discontinuous function by the hyperbolic tangent function, the chattering effect has also been highly reduced.

The main contribution of this paper is to develop a new flowmeter fault detection approach based on optimized non-singleton type-3 (NT3) fuzzy logic systems (FLSs). The introduced method is implemented on an experimental gas industry plant. The system is modeled by NT3FLSs, and the faults are detected by comparison of measured end estimated signals. In this scheme, the detecting performance depends on the estimation and modeling performance. The suggested NT3FLS is used because of the existence of a high level of measurement errors and uncertainties in this problem. The designed NT3FLS with uncertain footprint-of-uncertainty (FOU), fuzzy secondary memberships and adaptive non-singleton fuzzification results in a powerful tool for modeling signals immersed in noise and error. The level of non-singleton fuzzification and membership parameters are tuned by maximum correntropy (MC) unscented Kalman filter (KF), and the rule parameters are learned by correntropy KF (CKF) with fuzzy kernel size. The suggested learning algorithms can handle the non-Gaussian noises that are common in industrial applications. The various types of flowmeters are investigated, and the effect of common faults are examined. It is shown that the suggested approach can detect the various faults with good accuracy in comparison with conventional approaches.

In this study, a novel fast terminal sliding mode control technique based on the disturbance observer is recommended for the stabilization of underactuated robotic systems. The finite time disturbance observer is employed to estimate the exterior disturbances of the system and develop the finite time control law. The proposed controller can regulate the state trajectories of the underactuated systems to the origin within a finite time in the existence of external disturbances. The stability analysis of the proposed control scheme is verified via the Lyapunov stabilization theory. The designed control law is enough to drive a switching surface achieving the fast terminal sliding mode against severe model nonlinearities with large parametric uncertainties and external disturbances. Illustrative simulation results and experimental validations on a cart-inverted pendulum system are provided to display the success and efficacy of the offered method.