Model-Based Maneuvering Controls for Autonomous Underwater Vehicles

1992 ◽  
Vol 114 (4) ◽  
pp. 614-622 ◽  
Author(s):  
A. J. Healey

This paper proposes the development of a model following autopilot system for an Autonomous Underwater Vehicle (AUV) depth changing control. The parameters to command a maneuver are generated off-line and selected as appropriate by the vehicle’s autonomous control system. A series of such preprogrammed maneuvers can be stored in an on-board computer, and used as command generation systems for the autopilot. The paper presents a linear model following control (LMFC) design based on the open-loop linearized vehicle model as the reference model, a robustness analysis of the scheme and simulation results of response in the diveplane using the full nonlinear vehicle system equations. LMFC has been proposed for aircraft where certain desirable handling characteristics based on an arbitrary model are required or where decoupled control for Control Configured Vehicle (CCV) performance is needed. It is shown here that this model-based LMFC autopilot for underwater vehicles exhibits relatively robust behavior under conditions of parameter uncertainty and non-linearity which is not worse than the equivalent LQR/LTR for linear output feedback systems. Also, a tailored transient response is provided, conducive to near time optimal response.

2013 ◽  
Vol 278-280 ◽  
pp. 1473-1476
Author(s):  
Alexander Lebedev

New methods of the synthesis of multi-dimensional robust and adaptive control systems for the centralized control of the spatial motion of autonomous underwater vehicles (AUV) is developed in this paper, such as variable structure system (VSS) and self-adjustment system with reference model. The conditions of the sliding mode existence and the self-adjustment process stability with the presence of essential dynamic reciprocal effect between all control channels are obtained and strictly proved. The application of synthesized discontinuous control provides the high control quality at any variations of the object parameters within the given ranges.


Author(s):  
Mohammad Saghafi ◽  
Roham Lavimi

In this research, the flow around the autonomous underwater vehicles with symmetrical bodies is numerically investigated. Increasing the drag force in autonomous underwater vehicles increases the energy consumption and decreases the duration of underwater exploration and operations. Therefore, the main objective of this research is to decrease drag force with the change in geometry to reduce energy consumption. In this study, the decreasing or increasing trends of the drag force of axisymmetric bare hulls have been studied by making alterations in the curve equations and creating the optimal geometric shapes in terms of hydrodynamics for the noses and tails of autonomous underwater vehicles. The incompressible, three-dimensional, and steady Navier–Stokes equations have been used to simulate the flow. Also, k-ε Realizable with enhanced wall treatment was used for turbulence modeling. Validation results were acceptable with respect to the 3.6% and 1.4% difference with numerical and experimental results. The results showed that all the autonomous underwater vehicle hulls designed in this study, at an attack angle of 0°, had a lower drag force than the autonomous underwater vehicle hull used for validation except geometry no. 1. In addition, nose no. 3 has been selected as the best nose according to the lowest value of stagnation pressure, and also tail no. 3 has been chosen as the best tail due to the production of the lowest vortex. Therefore, geometry no. 5 has been designed using nose and tail no. 3. The comparison made here showed that the maximum drag reduction in geometry no. 5 was equal to 26%, and therefore, it has been selected as the best bare hull in terms of hydrodynamics.


2018 ◽  
Vol 212 (1) ◽  
pp. 105-123
Author(s):  
Tomasz Praczyk ◽  
Piotr Szymak ◽  
Krzysztof Naus ◽  
Leszek Pietrukaniec ◽  
Stanisław Hożyń

Abstract The paper presents the first part of the final report on all the experiments with biomimetic autono-mous underwater vehicle (BAUV) performed within the confines of the project entitled ‘Autonomous underwater vehicles with silent undulating propulsion for underwater ISR’, financed by Polish National Center of Research and Development. The report includes experiments in the swimming pool as well as in real conditions, that is, both in a lake and in the sea. The tests presented in this part of the final report were focused on low-level control.


2018 ◽  
Vol 213 (2) ◽  
pp. 53-67 ◽  
Author(s):  
Tomasz Praczyk ◽  
Piotr Szymak ◽  
Krzysztof Naus ◽  
Leszek Pietrukaniec ◽  
Stanisław Hożyń

Abstract The paper presents the second part of the final report on all the experiments with biomimetic autonomous underwater vehicle (BAUV) performed within the confines of the project entitled ‘Autonomous underwater vehicles with silent undulating propulsion for underwater ISR’, financed by Polish National Center of Research and Development. The report includes experiments on the swimming pool as well as in real conditions, that is, both in a lake and in the sea. The tests presented in this part of the final report were focused on navigation and autonomous operation.


2021 ◽  
Vol 2129 (1) ◽  
pp. 012080
Author(s):  
Chinonso Okereke ◽  
Nur Haliza Abdul Wahab ◽  
Mohd Murtadha Mohamad ◽  
S H Zaleha

Abstract Water, mostly oceans, covers over two-third of the earth. About 95% of these oceans are yet to be explored which includes 99% of the sea-beds. The introduction of the Internet of Underwater Things (IoUT) underwater has become a powerful technology necessary to the quest to develop a SMART Ocean. Autonomous Underwater Vehicles (AUVs) play a crucial role in this technology because of their mobility and longer energy storage. In order for AUV technologies to be effective, the challenges of AUVs must be adequately solved. This paper provides an overview of the challenges of IoUT, the contributions of AUVs in IoUT as well as the current challenges and opening in AUV. A summary and suggestion for future work was discussed.


2021 ◽  
Vol 29 (1) ◽  
pp. 97-110
Author(s):  
V.S. Bykova ◽  
◽  
A.I. Mashoshin ◽  
I.V. Pashkevich ◽  
◽  
...  

Two safe navigation algorithms for autonomous underwater vehicles are described: algorithm for avoidance of point obstacles including all the moving underwater and surface objects, and limited size bottom objects, and algorithm for bypassing extended obstacles such as bottom elevations, rough lower ice edge, garbage patches. These algorithms are developed for a control system of a heavyweight autonomous underwater vehicle.


Author(s):  
Xi-wen Ma ◽  
Yan-li Chen ◽  
Gui-qiang Bai ◽  
Yong-bai Sha ◽  
Jun Liu

We present a bionic neural wave network that uses multiple autonomous underwater vehicles to search and acquire intelligent targets in an unknown underwater environment. The neuron pheromone content is arranged according to neural wave diffusion and layer-by-layer energy attenuation, when underwater mesh space based on neural wave diffusion theory was established that the neuron nodes in the neural network structure correspond to obstacles, autonomous underwater vehicles, and targets in the environment. In order to solve the problems of over-allocation and under-allocation of the multi-autonomous underwater vehicles system during the cooperative capture of targets, a redistribution mechanism based on the improved self-organizing map algorithm is implemented and directed to rationalize task distribution. Two different taboo search methods are employed to update the autonomous underwater vehicle path in real time, and the polynomial coefficient solution method is used to fit partial path data. So that the autonomous underwater vehicle trajectory can be obtained and an interceptor position coordinate can be predicted. An auxiliary autonomous underwater vehicle is aimed to replace the intercepted autonomous underwater vehicle and the matching capture points are tracked to ensure the completion of the task so that the full range of hunting targets is identified. In order to simulate an unknown complex underwater environment, obstacles are randomly arranged around the target, the location information of the obstacle, and the target is unknown and unpredictable. Four simulation experiments were performed to verify the accuracy and efficiency of the algorithm under unknown environment. The results show that this algorithm can improve the path update average efficiency by 66% compared with other algorithms. Obviously, this algorithm is reasonable and effective.


2018 ◽  
Vol 35 (4) ◽  
pp. 797-808 ◽  
Author(s):  
Mario P. Brito ◽  
Gwyn Griffiths

AbstractAutonomous underwater vehicles (AUVs) have proven to be feasible platforms for marine observations. Risk and reliability studies on the performance of these vehicles by different groups show a significant difference in reliability, with the observation that the outcomes depend on whether the vehicles are operated by developers or nondevelopers. This paper shows that this difference in reliability is due to the failure prevention and correction procedures—risk mitigation—put in place by developers. However, no formalization has been developed for updating the risk profile based on the expected effectiveness of the failure prevention and correction process. A generic Bayesian approach for updating the risk profile is presented, based on the probability of failure prevention and correction and the number of subsequent deployments on which the failure does not occur. The approach, which applies whether the risk profile is captured in a parametric or nonparametric survival model, is applied to a real case study of the International Submarine Engineering Ltd. (ISE) Explorer AUV.


2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985318
Author(s):  
Zheng Cong ◽  
Ye Li ◽  
Yanqing Jiang ◽  
Teng Ma ◽  
Yusen Gong ◽  
...  

This article presents a comparison of different path-planning algorithms for autonomous underwater vehicles using terrain-aided navigation. Four different path-planning methods are discussed: the genetic algorithm, the A* algorithm, the rapidly exploring random tree* algorithm, and the ant colony algorithm. The goal of this article is to compare the four methods to determine how to obtain better positioning accuracy when using terrain-aided navigation as a means of navigation. Each algorithm combines terrain complexity to comprehensively consider the motion characteristics of the autonomous underwater vehicles, giving reachable path between the start and end points. Terrain-aided navigation overcomes the challenges of underwater domain, such as visual distortion and radio frequency signal attenuation, which make landmark-based localization infeasible. The path-planning algorithms improve the terrain-aided navigation positioning accuracy by considering terrain complexity. To evaluate the four algorithms, we designed simulation experiments that use real-word seabed bathymetry data. The results of autonomous underwater vehicle navigation by terrain-aided navigation in these four cases are obtained and analyzed.


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