The traditional underwater integrated navigation system is based on an optical fiber gyroscope and Doppler Velocity Log, which is high-precision but also expensive, heavy, bulky and difficult to adapt to the development requirements of AUV swarm, intelligence and miniaturization. This paper proposes a low-cost, light-weight, small-volume and low-computation underwater integrated navigation system based on MEMS IMU/DVL/USBL. First, according to the motion formula of AUV, a five-dimensional state equation of the system was established, whose dimension was far less than that of the traditional. Second, the main source of error was considered. As the velocity observation value of the system, the velocity measured by DVL eliminated the scale error and lever arm error. As the position observation value of the system, the position measured by USBL eliminated the lever arm error. Third, to solve the issue of inconsistent observation frequencies between DVL and USBL, a sequential filter was proposed to update the extended Kalman filter. Finally, through selecting the sensor equipment and conducting two lake experiments with total voyages of 5.02 km and 3.2 km, respectively, the correctness and practicality of the system were confirmed by the results. By comparing the output of the integrated navigation system and the data of RTK GPS, the average position error was 4.12 m, the maximum position error was 8.53 m, the average velocity error was 0.027 m/s and the average yaw error was 1.41°, whose precision is as high as that of an optical fiber gyroscope and Doppler Velocity Log integrated navigation system, but the price is less than half of that. The experimental results show that the proposed underwater integrated navigation system could realize the high-precision and long-term navigation of AUV in the designated area, which had great potential for both military and civilian applications.

The motion of an underwater vehicle is prone to be affected by time-varying model parameters and the actuator limitation in control practice. Adaptive control is an effective method to deal with the general system dynamic uncertainties and disturbances. However, the effect of disturbances control on transient dynamics is not prominent. In this paper, we redesign the $L_1$ adaptive control architecture (L1AC) with anti-windup (AW) compensator to guarantee robust and fast adaption of the underwater vehicle with input saturation and coupling disturbances. To reduce the fluctuation of vehicle states, the Riccati-based AW compensator is utilized to compensate the output signal from L1AC controller via taking proper modification. The proposed method is applied to the pitch channel of REMUS vehicle’s six Degrees Of Freedom (DOF) model with strong nonlinearities and compared with L1AC baseline controller. Simulations show the effectiveness of the proposed control strategy compared to the original L1AC. Besides, the fluctuation in roll channel coupled with pitch channel is suppressed according to the performances of control tests.

Spot hover and high speed capabilities of underwater vehicles are essential for ocean exploring, however, few vehicles have these two features. Moreover, the motion of underwater vehicles is prone to be affected by the unknown hydrodynamics. This paper presents a novel negative-buoyancy autonomous underwater vehicle equipped with tri-tilt-rotor to obtain these two features. A detailed mathematical model is derived, which is then decoupled to altitude and attitude subsystems. For controlling the underwater vehicle, an attitude error model is designed for the attitude subsystem, and an adaptive nonlinear controller is proposed for the attitude error model based on immersion and invariance methodology. To demonstrate the effectiveness of the proposed controller, a three degrees of freedom (DOF) testbed is developed, and the performance of the controller is validated through a real-time experiment.

In this paper, an intelligent control scheme of formation collision avoidance and iterative docking is proposed for full-actuated unmanned surface vehicles (USVs). The artificial potential field method is integrated into the partial differential equation (PDE) formation control approach, which can improve the collision-avoidance performance of the formation. During the docking process of the straight-line formation, the USV agent is expected to track the desired commands accurately. Considering the possibility of docking failure, an iterative learning model predictive control (ILMPC) scheme is introduced. Once the moving USV fails in docking on the stationary USV, the moving agent can return to the origin to re-execute the docking process. The ILMPC method has the advantages of model predictive control and the iterative learning, so it can consider the future process dynamics in the time domain and overcome periodic disturbances. Simulation results show that USVs can avoid collisions with each other in the straight-line-formation mission. Furthermore, the USV agent can dock one-by-one successfully when interference exists.

This paper proposes a Negative-buoyancy Quad Tilt-rotor Autonomous Underwater Vehicle (NQTAUV), for which an attitude-tracking controller is designed for the hover and transition modes based on a disturbance-rejection control scheme. First, the structure of NQTAUV is illustrated, a mathematical model based on the Rodrigues parameters is proposed, and the attitude-tracking error model is derived. To simplify the disturbance-observer design procedure, a disturbance observer with a single parameter was designed to estimate the disturbance torque acting on the vehicle. The controller was designed to track the target attitude, and the stability of the whole system is analyzed. Finally, the performance of the proposed method was validated by three experiments. The primary benefit of the proposed method is the simplicity of its tuning and implementation.