Wide bandwidth positioning systems for space and underwater vehicles

A tethered flight vehicle such as Subzero III can be a reliable test-bed for AUV control techniques provided that the tether effects be removed by feed-forward control. To achieve the composite control idea, a numerical scheme for prediction of tether effects has been proposed and assessed. We argue that the composite control scheme can also be applied to the control of an ROV during the deployment of the umbilical. The H∞ approach has been applied to the design of the autopilots for autonomous underwater vehicles. The autopilots developed have the following features: (1) they have simpler structures than conventional H∞ design and the performance degrada tion caused by the controller order reduction is negligible; (2) rate feedback is applied for heading and depth control to improve tracking performance; (3) the overshoot specification is considered in the design by choosing suitable weighting functions. The results of both nonlinear simulations and water trials in two different tanks show that the autopilots are robust to model uncertainty, external disturbances and varying dynamics of the vehicle and exhibit good tracking performance. Thus the effectiveness of robust control for AUVs appears promising.

Hydrodynamic coefficient estimation is crucial to the shape design, dynamic modeling, and control of underwater vehicles. In this paper, we conduct a numerical study on the hydrodynamic coefficient estimation of an underactuated underwater vehicle (actuated only in the surge, heave, and yaw degrees of freedom) by adopting the computational fluid dynamics (CFD) approach. Firstly, the mechanical structure of an underactuated underwater vehicle is briefly introduced, and the dynamic model of the underwater vehicle with hydrodynamic effects is established. Then, steady and unsteady Reynolds Averaged Navier–Stokes (RANS) simulations are carried out to numerically simulate the towing test, rotating arm test, and Planar Motion Mechanism (PMM) test of the underwater vehicle numerically. To simulate unsteady motions of the underactuated underwater vehicle, a sliding mesh model is adopted to simulate flows in the computational fluid domain that contain multiple moving zones and capture the unsteady interactions between the underwater vehicle and the flow field. Finally, the estimated hydrodynamic coefficients of the underwater vehicle are validated in a physical experiment platform, and the results show that the numerical estimates are in good agreement with the experimental data.

In this chapter, the receding horizon Kalman filter is applied to underwater navigation systems. The ocean covers about two-thirds of the earth and has a great effect on human beings. However, the ocean is overlooked while we focus our attention on land and atmospheric issues; we have not been able to explore the full depths of the ocean, its abundant livings and non-living resources. For example, only recently we have discovered, by using manned submersibles, that a large amount of methane and carbon dioxide comes from the seafloor and extraordinary groups of organisms live in hydrothermal vent areas. However, a number of complex issues due to the unstructured and hazardous undersea environment make it difficult to survey in the ocean even though today’s technologies have allowed humans to land on the moon and robots to travel to Mars. Unmanned underwater vehicles (UUVs) can help us better understand marine and other environmental issues, protect the ocean resources of the earth from pollution, and efficiently utilize them for human welfare. The UUV is a platform for a variety of sensors: acoustic, magnetic, gravimetric and chemical ones. Most commercial UUVs are tethered and remotely operated, referred to as remotely operated vehicles (ROVs). Extensive use of manned submersibles and ROVs are currently limited to a few applications because of very high operational costs, operator fatigue and safety issues. The demand for advanced underwater vehicle technologies is growing and will eventually lead to fully autonomous and reliable underwater vehicles. Autonomous underwater vehicles (AUVs) were initially developed to perform missions that were not easy for ROVs and manned underwater vehicles. Since the autonomy allows AUVs to be used for risky missions such as a mine countermeasure (MCM) or under-ice operations, AUVs are replacing ROVs towed vehicles as well as manned underwater vehicles (Whitcomb, 2000). For detailed ocean surveys, an AUV acts as a more stable platform for precision sensors than ROVs or towed vehicles because an AUV is not subject to physical disturbances transmitted along the cable to the surface vessel. This absence of physical attachment also allows AUVs to measure ocean characteristics at specific depths and perform bottom-following missions as owing to its autonomy. In short, An AUV provides marine researchers with a new form of access to deeper ocean. For an AUV to successfully complete a typical survey mission, it must follow a path specified by the operator as closely as possible and arrive at a precise location for collecting data. When an AUV is not able to follow the path accurately during the mission, critical Source: Kalman Filter, Book edited by: Vedran Kordic, ISBN 978-953-307-094-0, pp. 390, May 2010, INTECH, Croatia, downloaded from SCIYO.COM

Unmanned Underwater Vehicles have gained popularity for the last decades, especially for the purpose of not risking human life in dangerous operations. On the other hand, underwater environment introduces numerous challenges in control, navigation and communication of such vehicles. Certainly, this fact makes the development of these vehicles more interesting and engineering-wise more attractive. In this review study, among the mentioned problems, we focus on the control of underwater vehicles, particularly the motion control. We try to summarize the evolution of the underwater vehicle motion control studies throughout the last two decades, and classify them.

Unmanned underwater vehicles (UUVs) have become increasingly popular in recent years due to their use in various applications. The motivations for using UUVs include the exploration of difficult and dangerous underwater environments, military tasks in mine detection, intelligence gathering and surveillance, the inspection of offshore oil and gas infrastructure in the oil and gas industry, scientific research for studying marine life, and the search and rescue of missing persons or submerged airplanes or boats in underwater environments. UUVs offer many advantages in achieving the desired applications with increased safety, efficiency, and cost-effectiveness. However, there are also several challenges associated with their communication, navigation, power requirements, maintenance, and payload limitations. These types of vehicles are also prone to various disturbances caused by currents of the ocean, propulsion systems, and unmolded uncertainties. Practically, it is a challenging task to design a controller that will ensure optimal performance under these conditions. Therefore, the control system design is of prime importance in the overall development of UUVs. Also, the UUV controller receives input from different sensors, and the data from these sensors are used by the controller to perform different tasks. The control systems of UUVs should take into account all uncertainties and make them stable so that all sensors can perform optimally. This paper presents a complete review of different control system design algorithms for UUVs. The basic logic designs of several control system algorithms are also presented. A comparison is made based on reliability, robustness, precession, and the ability of the controller to handle the nonlinearity that is faced by UUVs during their missions. Simulation and experimental results are thoroughly studied to gain insight into each algorithm. The advantages and disadvantages of each algorithm are also presented, which will facilitate the selection of a suitable algorithm for the control system design of UUVs.

The problem of designing an accurate and reliable control for an Autonomous Underwater Vehicle (AUV), which is being subjected to environmental disturbances as well as configuration related changes, is critical in order to accomplish a successful mission. Any real-world problem solving system must deal with the issue of uncertainty, since the system's knowledge of the world is always incomplete, imprecise, and uncertain. This situation is aggravated for an AUV, due to the complex oceanic environment, and the inevitable noise of the sensory system. Some major facts that contribute to the difficulty of the underwater vehicle control are: • the dynamic behavior of the vehicle is highly nonlinear, • hydrodynamic coefficients cannot be easily obtained, hence making up uncertainties in the model knowledge, • the vehicle main body can be disturbed due to the ocean currents and vehicle motion. Therefore, it is difficult to obtain high performance by using the conventional control strategies. The control system should be able to learn and adapt itself to the changes in the dynamics of the vehicle and its environment. Many control methods have been proposed by researchers during the last decade, and there still exists a trend towards finding a better control law to achieve exponential stability while accounting for environmental changes and vehicle uncertainties. Focusing on the low level motion control of AUVs, most of the proposed control schemes take into account the uncertainty in the model by resorting to an adaptive strategy ((Corradini & Orlando, 1997), (Fossen & Sagatun, 1991a) and (Narasimhan & Singh, 2006)), or a robust approach ((Marco & Healey, 2001) and (Healey & Lienard, 1993)). In (Healey & Lienard, 1993) an estimation of the dynamic parameters of the vehicle NPS AUV Phoenix is also provided. Other relevant works on the adaptive and robust control of underwater vehicles are (Cristi & Healey, 1989), and (Cristi et al., 1990). (Leonard & Krishnaprasad, 1994) considers the control of an AUV in the event of an actuator failure. Experimental results on underwater vehicle control have been addressed by many researchers (e.g. see (Antonelli et al., 1999), (Antonelli et al., 2001), and (Zhao & Yuh, 2005)). An overview of control techniques for AUVs is reported in (Fossen, 1994). The aim of this chapter is to design a control system that would achieve perfect tracking for all configuration variables (e.g. sway and yaw motions) for any desired trajectory. To this end, we present the application of nonlinear control methods to an AUV that would lead to O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg

Nowadays, the increasing availability of commercial off-the-shelf underwater acoustic and non-acoustic (e.g., optical and electromagnetic) modems that can be employed for both short-range broadband and long-range low-rate communication, the increasing level of autonomy of underwater vehicles, and the refinement of their underwater navigation systems pave the way for several new applications, such as data muling from underwater sensor networks and the transmission of real-time video streams underwater. In addition, these new developments inspired many companies to start designing hybrid wireless-driven underwater vehicles specifically tailored for off-shore operations and that are able to behave either as remotely operated vehicles (ROVs) or as autonomous underwater vehicles (AUVs), depending on both the type of mission they are required to perform and the limitations imposed by underwater communication channels. In this paper, we evaluate the actual quality of service (QoS) achievable with an underwater wireless-piloted vehicle, addressing the realistic aspects found in the underwater domain, first reviewing the current state-of-the-art of communication technologies and then proposing the list of application streams needed for control of the underwater vehicle, grouping them in different working modes according to the level of autonomy required by the off-shore mission. The proposed system is finally evaluated by employing the DESERT Underwater simulation framework by specifically analyzing the QoS that can be provided to each application stream when using a multimodal underwater communication system specifically designed to support different traffic-based QoSs. Both the analysis and the results show that changes in the underwater environment have a strong impact on the range and on the stability of the communication link.

The development of a practical motion planning and control algorithm for under-actuated robots in an unknown disturbance is a very important issue in robotics research. In the case of under actuated underwater vehicles, developing such an algorithm has been particularly problematic for several reasons. First, not only the kinematical characteristics of the motion but also the dynamical characteristics of the underwater vehicle must be considered in the motion planning calculation. Second, it is very difficult to ascertain the exact distribution of the velocity of non-uniform sea flow around obstacles on the seabed before the mission. Third, the effect of the sea flow on the motion of an underwater vehicle is very large because the speed of sea flow is very high compared with the vehicle's. This paper proposes a new method based on the application of reinforcement learning to solve these problems. Reinforcement learning based on the Markov decision process (MDP) is known to be suitable for acquiring motion control algorithms for robots acting in a stochastic environment with disturbance. However, to apply reinforcement learning method, the robot's motion must be suitably digitized and the learning environment must be equal to the robot's mission environment. This paper introduces a motion digitizing method based on an artificial neuron model and a method for making up for the difference between learning and mission environments. The performance of the proposed algorithm is examined by the dynamical simulation of an under-actuated underwater vehicle cruising in an environment with an obstacle and an unknown non-uniform flow simulated by potential flow.

Vehicle mobile movement can cause dynamic error of the platform inertial navigation system (PINS) which is widely used in underwater vehicle. Taking PINS as the research object, the space motion mathematical models of underwater vehicle are analyzed and established by reasonable simply. Through coordinate transformation relationship research of the fixed coordinate system, the moving coordinate system and the local present coordinate system, the underwater vehicle actual space motion can be embedded in the PINS. It can provide PINS the input information which contain the east and north acceleration real-timely by controlling vehicle motion and get the navigation which is more close to underwater actual motion. Thus the whole PHINS simulator based on underwater vehicle motion model are realized. Computer simulation result show the embedded method is right and the PINS simulator can realized the actual simulation well. This is a new good method for the movement adaptability examination of INS.

This paper is concerned with the security sliding mode-based leader-following control of multiple autonomous unmanned underwater vehicles (AUVs) system subject to stochastic DoS attacks. Firstly, a Bernoulli variable is used to describe the phenomenon of stochastic DoS attacks between controllers and actuators, and the attack probability is known for controller design. Secondly, the closed-loop system is established by taking the integral sliding mode control scheme and stochastic DoS attacks into account. Then, the conditions of stochastic stability for system are given by using the stochastic systems analysis method and the model decomposition technique. In the simulation part, a group of AUVs models is used to verify the validity of the proposed state consensus control scheme. The simulation example shows that all the state can achieve consensus even in presence of randomly launched DoS attack.

This paper investigates a trajectory tracking control method for multi-underactuated underwater vehicle (AUV) formations with uncertain model parameters and external environmental disturbances. Firstly, a dual closed-loop fixed-time integral sliding mode controller is designed. By combining fixed-time theory and integral sliding mode control, this controller ensures the stability of the formation tracking and guarantees the convergence of the tracking error to zero within a fixed time duration. Secondly, an adaptive radial basis function (RBF) neural network controller is integrated with a conditional integrator to address uncertainties in model parameters, approximation errors, and external environmental disturbances in practical multi-AUV systems. This controller exhibits robustness and adaptivity. Additionally, a virtual leader strategy is employed to enhance the robustness of the formation system and prevent formation collapse caused by leader AUV failures. Finally, simulation results validate the effectiveness of the proposed formation controller, demonstrating accurate trajectory tracking by the AUV formation.

FORMATION CONTROL OF AUTONOMOUS UNDERWATER VEHICLES

This paper focuses on enhancing target tracking techniques for unmanned underwater vehicles (UUVs) used for deep-sea exploration, especially for the latest advances in digital technology. The article begins with an innovative UUV target tracking algorithm improvement based on the correlation filtering algorithm. Introducing the spatio-temporal regularization method and penalty function optimizes the filter parameters and enhances the algorithm’s performance. Then, a new objective function is constructed by combining the optimal feature weights and baseline function calculated by the dynamic feature weighting method, which effectively excludes the influence of interference peaks in the algorithm. In addition, by applying the Gaussian correlation method, the article further improves the algorithm’s robustness. When the obstacle avoidance ability of the algorithm is analyzed, it is found that the control error of the obstacle avoidance speed in both X and Y directions is less than 0.1 m/s, and the difference between the actual angle and the desired angle of the attitude angle is less than 0.5 degrees. This indicates that the algorithm can effectively avoid all obstacles and accurately track the target. The target tracking experiments show that the tracking performance scores of the algorithm are generally higher than 9, and the tracking accuracy is more than 95%, which is significantly better than other existing algorithms. The optimized tracking algorithm proposed in this paper not only provides essential technical support for the development of unmanned underwater vehicle technology, but also provides valuable reference for the future application and practice of the algorithm.

Unmanned underwater vehicles (ROV/AUV) are autonomous or remotely controlled robotic systems that can move underwater at any desired angle. Unmanned underwater vehicles; It is used in areas such as underwater image taking, ship maintenance and repair, coast guard, examination of shipwrecks, underwater cleaning. In this study, the software design of the balance control of underwater vehicles was carried out using the PID algorithm. For the PID algorithm trial, a two-motor test setup with an IMU sensor was prepared. After the data from the sensor were recorded in MATLAB using the Kalman filter, the transfer function of the system was obtained using the System Identification Toolbox. With the obtained transfer function, the stable operation of the system is provided in real time. As a result of the research on software and hardware integration, microcontroller ARM-based STM32 was used.

*Agency for Defence Development, Jinhae, Korea**Graduate School of Korea Maritime University, Busan, Korea***Department of Ocean Engineering, Korea Maritime University, Busan, KoreaKEY WORDS: Cylindrical shell 원통형 구조물, High frequency vibration 고주파 진동, Excitation 가진, Noise 소음, Underwater vehicle 수중운동체ABSTRACT: Underwater vehicles such as UUVs (Unmanned Underwater Vehicles) and ROVs (Remotely Operated Vehicles) use sonar to detect their underwater environment or other underwater vehicles. The underwater vehicles designed recently have an electrical power system with high rotational speed. This system can generate high frequency vibra tions above 10 kHz, and these vibrations can cause bad (negativ e) effects on the performance of the sonar. In many previous investigations, nume rical analyses have been used for high frequency vibration prob lems. In this study, an experimental analysis was carried out, and a circular cylind rical shell was considered as the hull structure of an underwat er vehicle. Frequency transfer functions for the circular cylindrical shell were iden tified using an experimental vibration analysis in the air and in a fully-submerged condition. We compare the frequency transfer functions in the a ir and water to obtain hydro-elastic effects. It is found that the dynamic characteristics of the circular cylindrical shell are changed b y varying the response position.교신저자 박한일: 부산광역시 영도구 동삼 2동, 051-410-4326, hipark@hhu.ac.kr본 연구는 20011년 6월 개최된 한국해양과학기술협의회 공동학술대회에 발표된 논문을 근간으로 하고 있음을 밝힙니다 .