Motion parameter optimization for gliding strategy analysis of underwater gliders

Military forces of every country are trying their best to protect their motherland from the attackers. With advancement in marine technology, it has become critical to detect and track the target by obtaining active measurements before it is close enough to attack. The utilization of unmanned underwater vehicles for target tracking behavior is gaining great attention due to continuous advancement of underwater vehicular technology. Nevertheless, safe and stable communications issues among different acoustic devices are still under active investigation to reach a robust, secure, and flexible underwater networking. Moreover, due to harsh underwater environment, acoustic simulations are also time-consuming; therefore, an accurate model for target detection and tracking is a necessity. Apart from the harsh environment of underwater networks, various technologies emerging for terrestrial networking are also becoming the part of underwater networking. For instance, cognitive acoustic networks, software-defined networks, network function virtualization, cloud computing, fog computing, and internet of underwater things; all are leading to trusted next-generation underwater networks. In this paper, we first provide a comprehensive survey of unmanned underwater vehicles and different ray tracing models essential in target detection and tracking that answers several questions regarding the current necessities of underwater networks and finally, provides a solution that opens several doors for research community to excel in this area.

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An Overview of Next-Generation Underwater Target Detection and Tracking: An Integrated Underwater Architecture

A robust adaptive fuzzy neural network control (RAFNNC) algorithm is proposed based on a generalized dynamic fuzzy neural network (GDFNN), proportion-integral-differential (PID), and improved bacterial foraging optimization (BFO) algorithm, for heading the control of the unmanned marine vehicle (UMV) in the presence of a complex environment disturbance. First, the inverse dynamic model of the motion control of UMV is established based on the GDFNN for the uncertain disturbance caused by the complex environment disturbance. Then, the adaptive rate of the fuzzy neural network is designed based on the error between the real UMV heading angle and designed reference heading angle, so as to further adjust the weight parameter of the GDFNN, and then, the output control value of the neural network is obtained. In order to further reduce the computation amount and computation time of the RAFNNC, the parameters of the PID control algorithm were optimized in advance by using the improved BFO algorithm. The fractal dimension step size and the intelligent probe operation are integrated into the BFO algorithm, in order to optimize the operation time and accuracy of the algorithm. Stability of the designed RAFNNC algorithm for the heading control of the UMV in the presence of complex marine environment disturbance is proved by the Lyapunov stability theory, and the effectiveness and accuracy of the control algorithm proposed are verified by semi-physical simulation experiment carried out in our laboratory.

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Heading Control of Unmanned Marine Vehicles Based on an Improved Robust Adaptive Fuzzy Neural Network Control Algorithm

Adaptive robust sliding mode control of autonomous underwater glider with input constraints for persistent virtual mooring

Autonomous marine vehicles (AMVs), including autonomous surface and underwater vehicles, are versatile means to explore, exploit, monitor, and protect marine resources and environments. Motion control is a fundamental enabling technique for state-of-the-art AMV development. Especially, guidance is a critical component in AMV motion control. In recent years, line-of-sight (LOS) guidance, as an efficient guidance method, has attracted tremendous interest from both theoretical and practical perspectives. In this paper, an overview of recent advances in LOS guidance for AMV path following is provided. First, a control objective for the path following of an AMV with a kinematic model is specified. Next, major LOS guidance laws for path following are reviewed in detail. Then, LOS guidance laws applicable to coordinated path following of multiple AMVs are elaborated. Finally, six challenging issues for future research are addressed.

Advances in Line-of-Sight Guidance for Path Following of Autonomous Marine Vehicles: An Overview

The hybrid path planning algorithm based on improved A* and artificial potential field for unmanned surface vehicle formations

The underwater glider changes its direction to follow the preset path in the horizontal plane only by flapping its vertical rudder. Heading tracking control plays the core role in the navigation process. To deal with non-linear flow disturbance and saturation in actuator, a new hybrid heading tracking control algorithm was presented, which integrated an adaptive fuzzy incremental PID (AFIPID) and an anti-windup (AW) compensator to improve the adaptability and robustness of underwater glider's heading control. The dynamic model of an underwater glider named as Petrel-II 200 was modeled to serve as a controlled plant. The proposed heading tracking control algorithm was described in detail, where the rudder angle, a control quantum to the controlled plant were calculated to get forces and moments required for the desired glider heading. A closed loop motion control system with desired heading angle as input and actual heading angle output was put forward, which included the dynamic model of the Petrel-II 200 and the given heading tracking control algorithm. The simulations followed three typical mathematical signals and the experimental tests were carried out by taking in the dynamic parameters of the controlled plant. And the effectiveness of the proposed control algorithm was assessed and verified.

Heading tracking control with an adaptive hybrid control for under actuated underwater glider.

Adaptive path following control for Wave gliders in time-varying environment

Turning Maneuverability is an important hydrodynamic performance of the wave glider, which can realize the position keeping, path tracking and steering obstacle avoidance in a reliable way. The inf...

Research on turning maneuverability of submerged glider of the wave glider

The invention discloses an omnidirectional stable buoy used for data calibration of a glider for observing waves of a sea-air interface. The buoy comprises a gimbal, a connecting rod I, an electricalsealing chamber, a connecting rod II and a ballast weight which are coaxially and vertically arranged from top to bottom in sequence; observing equipment with a lower gravity center is carried on thegimbal, solar panels are arranged around the electrical sealing chamber, and a data acquisition module, a GPS positioning module, a satellite communication module, a data storage module and a controlmodule are installed in the electrical sealing chamber; the data acquisition module receives data of the observation equipment and GPS positioning module and is in wireless communication with a shore-based monitoring center through the satellite communication module to achieve data transmission or transmit the data to the data storage module for storage; an oblong floating body is fixedly and coaxially installed on the connecting rod II, and a mooring system is connected to the bottom of the ballast weight. The buoy has high stability and can obtain the high-precision observation data of the sea-air interface.

Hongqiang Sang

Papers

The hybrid path planning algorithm based on improved A* and artificial potential field for unmanned surface vehicle formations

Heading tracking control with an adaptive hybrid control for under actuated underwater glider.

Adaptive path following control for Wave gliders in time-varying environment

Research on turning maneuverability of submerged glider of the wave glider

Omnidirectional stable buoy used for data calibration of glider for observing waves of sea-air interface