Adaptive region tracking control for autonomous underwater vehicle

This paper describes research on remote monitoring and control of autonomous underwater vehicles (AUVs). This work is part of a larger effort to create autonomous ocean sampling networks (AOSN), a new concept for collecting synoptic oceanographic data. AOSN is based on the operation of small, low cost autonomous underwater vehicles (AUVs) within an array of moorings that provide communication and power-supply nodes. Critical to the realization of AOSN will be the ability to control these assets and monitor the data collection process remotely. During the time in which our AOSN partners have been developing acoustic communications, our laboratory has performed a variety of remote monitoring and control experiments to test different types of network distributed control software. Experimental results are presented for runs in the Charles River in which a radio modem towed on a float was used to monitor and control the vehicle from a workstation on the Internet. In addition, we have used our acoustic navigation system to send simple command messages to an Odyssey vehicle, achieving simultaneous control of multiple AUVs operating in a high current environment in the Haro Strait.

AUV position tracking and trajectory control based on fast-deployed deep reinforcement learning method

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.

A practical design method is developed for path following and coordinated control of Autonomous Underwater Vehicles (AUVs). Each AUV is modeled by a system with time-varying parameters, unknown nonlinear dynamics and unknown disturbance. A robust adaptive distributed controller is designed for each AUV such that all AUVs ultimately synchronize to the desired paths with required formation. Moreover, these controllers are distributed in the sense that the controller design for each AUV only requires relative state in formation between itself and its neighbors. Finally, a simulation example demonstrates the effectiveness of the control method.

Design for three-dimensional stabilization control of underactuated autonomous underwater vehicles

Underwater control applications, such as control of Autonomous Underwater Vehicles (AUV)s, have recently gained significant interest, and there is a growing demand for high-speed wireless communication between AUVs and base station. Acoustic communication provides low data rates and high propagation delays, both of which are not suitable for employing high control gains for the navigation of AUVs. On the other hand, Radio Frequency (RF) communication provides high data rate, but it is constrained by high attenuation due to high conductivity and permittivity of water resulting in a short working range. In this work, we propose an underwater networked control system with acoustic and RF hybrid communication, where an acoustic link is employed for long range communication and RF link is applied in close range. Our performance results indicate that the acoustic and RF hybrid communication system takes up to 38.5% less time to dock, up to 91% smaller steady state error and spends up to 39% lower communication energy as compared to the acoustic only system at the expense of up to 22.35% higher motive energy.

This paper deals with the control of underactuated autonomous underwater vehicles (AUVs). AUVs are needed in many applications such as the exploration of oceans, scientific and military missions, etc. There are many challenges in the control of AUVs due to the complexity of the AUV model, the unmodelled dynamics, the uncertainties and the environmental disturbances. A trajectory tracking control scheme is proposed in this paper; this control scheme is designed using the sliding mode control technique in order to be robust against bounded disturbances. The control performance of an example AUV, using the proposed method, is evaluated through computer simulations. These simulation studies, which consider different reference trajectories, show that the proposed control scheme is robust under bounded disturbances.

The absence of global positioning system (GPS) signals and the influence of ocean currents are two of the main challenges facing the autonomy of autonomous underwater vehicles (AUVs). This paper proposes an acoustic localization-based tracking control method for AUVs. Particularly, three buoys that emit acoustic signals periodically are deployed over the surface. Times of arrivals of these acoustic signals at the AUV are then obtained and used to calculate an estimated position of the AUV. Moreover, the uncertainties involved in the localization and ocean currents are handled together in the framework of the extended Kalman filter. To deal with system physical constraints, model predictive control relying on online repetitive optimizations is applied in the tracking controller design. Furthermore, due to the different sampling times between localization and control, the dead-reckoning technique is utilized considering detailed AUV dynamics. To avoid using the highly nonlinear and complicated AUV dynamics in the online optimizations, successive linearizations are employed to achieve a trade-off between computational complexity and control performance. Simulation results show that the proposed algorithms are effective and can achieve the AUV tracking control goals.

The control of autonomous underwater vehicles has been a challenge to control engineers due to combined nonlinear nature of both the vehicle itself and the environment in which they operate. This paper presents an implementation research on the adaptive controller of an autonomous underwater vehicle testbed in which the controller architecture is made using multilayered neural networks. The problem considered is that of designing a controller for an autonomous underwater vehicle to provide directional control. A flux gate compass is used to measure the yaw angle and yaw rate. Directional control is performed by two thrusters in the horizontal plane. Weight adaptation of the neural network is achieved by minimizing an objective function that is weighted sum of tracking errors and control input rates. According to the experimental tests on various command trajectories, we show that when the learning process is kept active through the control operation, the neural network adapts to time-varying plant dynamics as well as disturbance upsets.

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 article presents a design method for the three-dimensional trajectory tracking control of an underactuated autonomous underwater vehicle with unknown current disturbances. To simplify the complexity of the controller and avoid the singular problem induced by initial state constraints, a novel nonlinear backstepping technique based on virtual control variables is employed to design the kinematics and dynamics controllers. The control law is developed by building virtual errors, which can solve the problem of differential explosion in the traditional backstepping. Specifically, an ocean current observer based on the kinematics model is proposed to estimate unknown current disturbances, where the estimation is integrated into the autonomous underwater vehicle kinematics and dynamics equations. The convergence of tracking errors and system stability are proven by using Lyapunov stable theory. Finally, the simulation studies were provided to illustrate the effectiveness and good performance of the above trajectory tracking strategy.

The underwater environment severely constrains robotic navigation and communications, making the use of traditional multi-robot control and coordination schemes very difficult. These challenges are exacerbated on a new generation of low-cost autonomous underwater vehicles (AUVs) that lack a Doppler velocity log, acoustic modem, or high-end inertial sensors typically used for underwater robotic navigation and communications.This letter demonstrates multi-robot operations for low-cost AUVs via a novel and user-friendly operating paradigm that allows intuitive command and control of an AUV group. Each vehicle is equipped with a low-power and inexpensive acoustic system for navigation and receipt of operator commands. This system consists of a passive array of hydrophones and a timed acquisition and data processing stack that allows each AUV to self-localize relative to a time-synchronized acoustic beacon. Switching between different operational “modes” on the beacon causes it to broadcast different acoustic signals which, when received by the AUVs, result in the vehicles switching between different autonomous behaviors. These behaviors are defined in a beacon-centric coordinate system using pre-defined parameters unique to each vehicle; as a result, the movement of the beacon itself allows the operator to control the group-wide movement of all vehicles concurrently. This letter presents field experiments with three SandShark AUVs in which operational mode and beacon movement were controlled by an operator. However, by installing the beacon on an autonomous vehicle, this paradigm would provide a method for remote command and control of an arbitrarily large number of miniature, low-cost AUVs, without the need for sophisticated navigational sensors or acoustic modems.

This paper presents an adaptive PD control scheme for multiple autonomous underwater vehicles (AUVs). The proposed adaptive PD controller with uncertain gravitational and buoyancy forces requires only model of gravity and buoyancy regressor matrix and does not need any knowledge of inertia matrix, Coriolis and centripetal force, hydrodynamic damping and the parameters of the gravity and buoyancy forces of the AUVs. Hence, the proposed controller has the advantages of simplicity and ease of implementation. Collision and obstacles avoidance strategy using multi-layer region control is also discussed. Stability analysis of the system is presented with the aid of Lyapunov-like function. Simulation studies on AUVs with 6 degrees of freedom are presented to demonstrate the effectiveness of the proposed controller.

The cooperative control of marine vehicles finds many applications in a variety of marine missions and tasks. This paper investigates the receding horizon formation control problem of a feet of nonholonomic autonomous underwater vehicles (AUVs), in which the follower AUVs are required to keep a prescribed formation pattern with respect to the leader one. A novel optimization problem and a new receding horizon control (RHC) algorithm are proposed. Results on the feasibility of the receding horizon formation algorithm and on the stability of the closed-loop systems are provided. Simulation studies for the formation-keeping control of the nonholonomic AUVs are carried out, and the simulation results verifies the effectiveness of the proposed algorithm.

: In this research, our goal has been to develop hierarchical hybrid mission control architecture for autonomous systems illustrating its application to autonomous underwater vehicle (AUV), verify the logical correctness of the controller designed, look into the feasibility of simulating the operations executed by the AUV, and automate controller synthesis. The correct operation of a system we design is a requirement. The challenge to develop a hierarchical hybrid mission controller for underwater vehicle which facilitates modeling, verification, simulation and automated synthesis of coordinators has lead to research in this area. We have worked and are working on these issues with Applied Research Laboratory (ARL) at Pennsylvania State University (PSU) who have designed autonomous underwater vehicles for over 50 years primarily under the support of the U.S. Navy through the Office of Naval Research (ONR).