Adaptive dynamic event-triggered consensus control of multiple autonomous underwater vehicles

Improved dynamic event-triggered anti-unwinding control for autonomous underwater vehicles

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

In this study, a finite-time position consensus control problem is investigated for multiple autonomous underwater vehicle (AUV) systems within a directed communication network. Via the homogeneous control method, an adaptive finite-time consensus control protocol is proposed using the relative states of neighboring AUVs. The proposed adaptive control protocol is fully distributed as it does not use any global information of the communication network. Numerical simulations are carried out to validate the effectiveness of the proposed control protocol.

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.

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.

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.

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.

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 region tracking control for Autonomous Underwater Vehicle (AUV). The AUV is required to track a moving region to accomplish a given task. The desired target is specified as a region rather than a point so that the control effort used to track the region is minimal. In the applications where the accuracy is of utmost importance, the desired region can be chosen to be small so that the precision is not lost. The desired region can be scaled up or scaled down so that the AUV can adjust its position to suit the applications. A Lyapunov-like function is presented for the stability analysis. Simulation results on AUV with 6 degrees of freedom are presented to demonstrate the effectiveness of the proposed controller.

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

Path planning and formation control are two of the most significant concepts which can be considered in multi-vehicle systems and particularly in autonomous underwater vehicles (AUVs). The cooperative implementation of complicated commands would lead to desirable results and increase the probability of success in the missions. Due to the nonlinear dynamics and environmental conditions, the cooperative control of AUVs is a challenging topic. The developments in AUV applications demonstrate the significance of research and development in path planning and formation control. Unlike ground or aerial autonomous vehicles, this field of study has not attracted considerable attention and further exploration is required as a result. The present paper reviews the different structures of formation control in AUVs and discusses their advantages and disadvantages. Besides formation control, the cooperative path planning of AUVs along with the limitations specific to the cooperative structure is taken into consideration in the present study. Moreover, avoiding any obstacle collision and preventing any encounter between group members are considered as critical issues in the formation control and cooperative path planning. Some areas are still open to investigation as implied by the technological suggestions, which will facilitate future research. At the end of the article, a simulated sample is given of the triangular formation path planning for AUVs.

In this paper, an adaptive neural network (NN) trajectory tracking control scheme is developed for underactuated autonomous underwater vehicles (AUVs) subject to unknown dynamic parameters and unknown disturbances. A novel additional control based on Nussbaum function is proposed to handle the underactuation problem of AUVs. The radial basis function NNs with minimal learning parameter (MLP) are employed to online approximate the compounded uncertain item due to unknown dynamic parameters and unknown disturbances. On the basics of the above, an adaptive NN trajectory tracking control law is proposed using command filtered vector-backstepping design tool. As a result, the computational burden of the developed trajectory tracking control scheme is significantly reduced, Theoretical analysis indicates that the proposed control law can force the AUV track the desired trajectory and guarantee that all signals in the trajectory tracking closed-loop control system are bounded. Simulation results on an AUV verify the effectiveness of our developed control scheme.

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.