Control Of Autonomous Underwater Vehicle Research Articles

Resilient sliding mode control of multiple autonomous underwater vehicles under stochastic DoS attack

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.

A hybrid acoustic-RF communication framework for networked control of autonomous underwater vehicles: design and cosimulation

Underwater control applications, especially ones using autonomous underwater vehicles (AUVs) have become very popular for industrial and military underwater exploration missions. This has led to the requirement of establishing a high data rate communication link between base stations and AUVs, while underwater systems mostly rely on acoustic communications. However, limited data rate and considerable propagation delay are the major challenges for employing acoustic communication in missions requiring high control gains. In this paper, we propose a hybrid acoustic and RF communication framework for establishing a networked control system, in which, for long distance communication and control the acoustic link is used, and in the short range, the RF link is employed. Our scenario for testing implements a docking maneuver application, where a docking station determines the positions of the AUVs via acoustic or RF communication, and different medium access schemes are used for coordinating the transmission of the nodes according to the communication mode. Considering the full dynamics of the entire system for controlling the AUVs, the real-time behavior of the underwater networked control system is evaluated realistically using our proposed integrated cosimulation environment, which includes different simulators. Our performance results indicate that under calm water conditions, our proposed hybrid system reduces the docking time by 33% compared to the acoustic-only.

Quaternion-based finite-time fault-tolerant trajectory tracking control for autonomous underwater vehicle without unwinding

This brief disposes the finite-time anti-unwinding trajectory tracking control problem of the autonomous underwater vehicle (AUV) encountering model uncertainties, ocean disturbances and actuator failures. Primarily, the kinematic model of translational and rotational motions is depicted by unit quaternion in lieu of classical Euler angle such that the AUV’s dynamics could be globally and uniquely formulated. Subsequently, two finite-time control strategies are presented here to leave the state variables of AUV can converge to an adjustable region. Additionally, the adaptive laws could be applicable to the existence of actuator faults by utilizing a passive fault-tolerant technology. By integrating the initial value of the scalar quaternion into the sliding mode surface, the proposed controllers are characterized with anti-unwinding property. Then, with the application of hyperbolic tangent function, finite-time stability will be achieved for tracking errors without singularity. Stability of the closed-loop system is verified via the Lyapunov theorem. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed controllers.

Single critic network based fault-tolerant tracking control for underactuated AUV with actuator fault

This work investigates the fault-tolerant control problem for underactuated autonomous underwater vehicle (AUV), in which the actuator fault is addressed, that is the sophisticated and challenging problem. A single critic network based adaptive dynamic programming (ADP) is employed to construct a novel fault-tolerant control scheme combined with the backstepping method. Firstly, a virtual velocity control vector is designed based on the kinematic model of underactuated AUV using backstepping approach. The virtual velocity control vector is taken as the virtual velocity of the dynamic model of underactuated AUV. Secondly, an error tracking system is constructed to transform the fault-tolerant tracking control problem into the optimal control problem. Then an online policy iteration algorithm is designed based on the estimated system states. Based on Lyapunov approach, the stability of the error tracking system is guaranteed by the proposed controller. Finally, the simulation results are shown to verify the effectiveness of the proposed method in this work.

Observation reconstruction and disturbance compensation-based position control for autonomous underwater vehicle

To address the position control problem of a six degrees of freedom autonomous underwater vehicle (AUV), the disturbance is observed by an observer and compensated by a controller in this paper. To ensure the vehicle reaches the specified position quickly, the sine cosine algorithm with individual memory is used to find suitable parameters for different controllers. The simulation results show that the observer can extract the system's internal and external uncertainty information in real-time, reduce the phase lag and improve the stability of AUV position control. For a system with complex nonlinearity such as AUV, the observer proposed in this paper has stronger applicability and better robustness.

Research on Formation Control Method of Heterogeneous AUV Group under Event-Triggered Mechanism

The time-sampling control strategy has communication discontinuities in the control of multiple AUVs (autonomous underwater vehicles). To overcome this problem, a distributed event-triggered communication mechanism is proposed to make each AUV communicate only when its own state is updated, which reduces the frequency of communication and improves the stability. This mechanism has better adaptability for formation control between heterogeneous AUV groups. At the same time, two consistency control algorithms based on event-triggered for homogeneous and heterogeneous AUV groups are studied, respectively. The known consistency algorithms are applied to the control of heterogeneous AUV groups for comparative analysis. The simulation results demonstrate that the number of communication among AUVs under the event-triggered control strategy can be significantly reduced. Therefore, the stability of the system is improved. Compared with the traditional consensus algorithm, the algorithm proposed in this paper has advantages in the control of heterogeneous AUV groups.

Fuzzy linear extended states observer‐based iteration learning fault‐tolerant control for autonomous underwater vehicle trajectory‐tracking system

To deal with thrusters’ faults of autonomous underwater vehicle (AUV), an iterative learning algorithm fault-tolerant control (FTC) based on the linear extended states observer (LESO) is proposed. In this control scheme, the non-linear feedback mechanism of the LESO is transplanted into iterative learning processes to estimate fault. Compared to our previous work, LESO is used to substitute classic non-linear extended state observer to make the establishment of the whole system more structured; moreover, the number of parameters need to be tuned can be reduced by the conception of observer bandwidth of LESO. To enhance the controllability and robustness of whole scheme, a new saturated sliding mode controller is proposed based on the Lyapunov theory. Then to achieve online parameter self-tuning for the control system, fuzzy logic controllers are introduced to find optimal relationship between LESO's parameter and tracking errors. The performance of the proposed controller is tested by some comparison experiments on Zhuhai A18D AUV; the results show that the proposed control scheme can ensure better stability than classical control and our previous control scheme when AUV suffers faults.

Trajectory tracking control for autonomous underwater vehicle based on rotation matrix attitude representation

This paper provides a rotation-matrix-based control scheme for fully actuated autonomous underwater vehicles (AUVs) considering model uncertainties and external disturbances. By resorting to the rotation matrix, AUV's attitude dynamics will be globally and uniquely represented without unwinding. However, this kind of attitude representation approach complicates the controller design process in the sense that the attitude tracking error is defined by a rotation matrix instead of a three-dimension vector. Regarding this, an alternative error vector is introduced for the simplicity of calculation and implementation. Then, a novel sliding mode surface that consists of two components is devised to provide the characters of finite-time convergence and singularity-free. Upon the application of this variable, an artful adaptive law is constructed such that the estimated information always appears as limited values in the controller. Eventually, theoretical analysis and comparative simulations can illustrate the effectiveness of the proposed control scheme.

Guidance and control of autonomous surface underwater vehicles for target tracking in ocean environment by deep reinforcement learning

This paper studies a guidance and control framework of multiple autonomous surface underwater vehicles (multi-ASUV) based on deep reinforcement learning (DRL) for target tracking. The framework enables the vehicles to complete the standoff tracking and sampling tasks in a predetermined circular trajectory centered on the target and maintain predetermined relative positions during the process to obtain high-precision spatio-temporal synchronization data. We design an end-to-end architecture that maps the sensor inputs to control commands and develop autonomous capable of achieving the hybrid objective of cooperative guidance, standoff tracking, and dynamic obstacle avoidance without having prior knowledge about the goal or the environment. The results demonstrate the feasibility of the end-to-end DRL method with higher accuracy than the traditional “guidance-control” two-step method. Meanwhile, the obstacle avoidance and standoff tracking experiment for swarm and the sampling experiment in the mesoscale eddy area are stimulated further to verify the proposed framework’s effectiveness and robust ability.

Synchronous-Clock Range-Angle Relative Acoustic Navigation: A Unified Approach to Multi-AUV Localization, Command, Control, and Coordination

This paper presents a scalable acoustic navigation approach for the unified command, control, and coordination of multiple autonomous underwater vehicles (AUVs). Existing multi-AUV operations typically achieve coordination manually by programming individual vehicles on the surface via radio communications, which becomes impractical with large vehicle numbers; or they require bi-directional intervehicle acoustic communications to achieve limited coordination when submerged, with limited scalability due to the physical properties of the acoustic channel. Our approach utilizes a single, periodically broadcasting beacon acting as a navigation reference for the group of AUVs, each of which carries a chip-scale atomic clock and fixed ultrashort baseline array of acoustic receivers. One-way travel-time from synchronized clocks and time-delays between signals received by each array element allow any number of vehicles within receive distance to determine range, angle, and thus determine their relative position to the beacon. The operator can command different vehicle behaviors by selecting between broadcast signals from a predetermined set, while coordination between AUVs is achieved without intervehicle communication by defining individual vehicle behaviors within the context of the group. Vehicle behaviors are designed within a beacon-centric moving frame of reference, allowing the operator to control the absolute position of the AUV group by repositioning the navigation beacon to survey the area of interest. Multiple deployments with a fleet of three miniature, low-cost SandShark AUVs performing closed-loop acoustic navigation in real-time provide experimental results validated against a secondary long-baseline positioning system, demonstrating the capabilities and robustness of our approach with real-world data.

Reinforcement learning-based saturated adaptive robust neural-network control of underactuated autonomous underwater vehicles

This paper studies a high-performance intelligent online adaptive robust saturated dynamic surface control framework for underactuated autonomous underwater vehicles by engaging Actor–Critic neural networks in the presence of unmodeled dynamics, uncertainties, ocean disturbances and actuator saturation. The proposed controller is designed based on reinforcement learning method to compensate the effects of unmodeled dynamics and uncertainties more accurately that can lead to a better performance for the controller. The Actor–Critic neural networks are trained real-time by designing online training laws creatively and a new critic function is proposed to supervise the closed-loop performance with the aid of the Critic neural network. The proposed structure for the reinforcement learning method benefits from a model-free algorithm and only relies on the measurable variables of the closed-loop control system. This independency from system dynamics results in considerable low computational burden for the controller and, hence, the proposed control algorithm is efficient computationally. The hyperbolic tangent function is ingeniously used as a saturated stabilizer term to bound the control signals that results in low-amplitude control action and the probability of actuator saturation phenomenon is minimized by learning and compensating the actuator saturation nonlinearity as well. Finally, the stability of the proposed closed-loop system is investigated by the Lyapunov’s direct methodology and simulations along a comparative study with some quantitative assessments certify the contributions of this paper.

Attitude Stabilization Control of Autonomous Underwater Vehicle Based on Decoupling Algorithm and PSO-ADRC.

Autonomous Underwater Vehicle are widely used in industries, such as marine resource exploitation and fish farming, but they are often subject to a large amount of interference which cause poor control stability, while performing their tasks. A decoupling control algorithm is proposed and A single control volume–single attitude angle model is constructed for the problem of severe coupling in the control system of attitude of six degrees of freedom Autonomous Underwater Vehicle. Aiming at the problem of complex Active Disturbance Rejection Control (ADRC) adjustment relying on manual experience, the PSO-ADRC algorithm is proposed to realize the automatic adjustment of its parameters, which improves the anti-interference ability and control accuracy of Autonomous Underwater Vehicle in dynamic environment. The anti-interference ability and control accuracy of the method were verified through experiments.

Depth Control of an Oil Bladder Type Deep-Sea AUV Based on Fuzzy Adaptive Linear Active Disturbance Rejection Control

The deep-sea autonomous underwater vehicle (AUV) is equipment of vital importance for ocean exploration, monitoring, and surveying. With a variable buoyancy system (VBS), AUV can achieve rising, diving, and hovering in the water column. This paper proposes a deep-sea AUV with an oil bladder type hydraulic VBS, which controls the oil flow rate with a proportional valve. However, the implementation of accurate depth control for AUV faces various challenges due to the varying water density with depth, the non-linear feature of the hydraulic system, and the disturbance from sea flows and currents. To tackle these problems, a third-order linear active disturbance rejection controller (LADRC) and its fuzzy adaptive version were designed and implemented in MATLAB/Simulink based on the state-space function of the proposed AUV system. Compared with the conventional PID controller, the simulation results indicate that the proposed LADRC controller shows strong robustness to disturbance, with other advantages including smaller steady-state error, overshoot, settling time, and response time. Moreover, the proposed fuzzy LADRC controller could further decrease the overshoot caused by the increasing target distance. The results prove that the designed depth controllers can meet the control requirements of the proposed deep-sea AUV.

Fixed-time sliding mode output feedback tracking control for autonomous underwater vehicle with prescribed performance constraint

This paper studies the trajectory tracking control problem for autonomous underwater vehicles (AUVs) subject to external disturbances and model uncertainties. To improve the tracking performance of the AUVs, a prescribed performance function is introduced to constrain the output tracking error. Then, a fixed-time extended state observer (FxTESO) is set up to estimate the unknown states and the lumped disturbances (including external disturbances and model uncertainties). With the outputs of the FxTESO, a novel dynamic fixed-time terminal sliding mode (FxTTSM) surface is constructed and then a fixed-time output feedback controller is designed to achieve trajectory tracking control for the AUVs. By employing Lyapunov function theory, the stability of the closed-loop system is analyzed. Simulation results are provided to verify the effectiveness of the developed control scheme.

Robust Path-Following Control of Underactuated AUVs with Multiple Uncertainties in the Vertical Plane

The current study employs a novel nonlinear robust control approach for path-following control of underactuated autonomous underwater vehicles (AUVs) with multiple uncertainties in the vertical plane. Firstly, a nonlinear underactuated AUV model is established to characterize the dynamics of AUV and path-following error. To resolve dependence on a detailed model that appeared in previous studies, the unknown time-varying attack angular velocity in the dynamic model of the path-following error is considered as the kinematic uncertainty, while the linear superposition of the external environmental disturbances, the perturbations in the internal model parameters, and other unmodeled dynamics in the dynamic model is chosen as lumped dynamic uncertainties. Several reduced-order extended state observers (ESOs) are designed for estimating both of these uncertainties. Secondly, to reduce the impact of input saturation and avoid the “explosion of complexity” associated with traditional back-stepping method, a nonlinear track differentiator (NTD) is utilized to follow the virtual control signal and its derivative. Thirdly, the constructed reduced-order ESOs and NTD are adopted to establish an augmented back-stepping controller, where its ability to stabilize the overall system is demonstrated using the Lyapunov theorem. Finally, extensive simulations and analyses in various working conditions, including the nominal working condition without disturbances, the working condition with multiple uncertainties, and the conditions which better replicate the actual environment, are performed to demonstrate the effectiveness, superiority, and robustness of the designed controller.

Simulation and control of a novel hovering type autonomous underwater vehicle (HAUV) with ballast tanks

Simulation and control of a novel hovering type autonomous underwater vehicle (HAUV) with ballast tanks

Reinforcement Learning based Parameter Optimization of Active Disturbance Rejection Control for Autonomous Underwater Vehicle

This paper proposes a liner active disturbance rejection control (LADRC) method based on the Q-Learning algorithm of reinforcement learning (RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle (AUV). The number of controllers is increased to realize AUV motion decoupling. At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller. Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.

Learning‐based robust control methodologies under information constraints

Learning‐based robust control methodologies under information constraints

Energy-optimal Planning and Control of Autonomous Underwater Vehicles Under Ocean Currents

Energy-optimal Planning and Control of Autonomous Underwater Vehicles Under Ocean Currents

Data-driven trajectory tracking control for autonomous underwater vehicle based on iterative extended state observer.

In this study, we explore the precise trajectory tracking control problem of autonomous underwater vehicle (AUV) under the disturbance of the underwater environment. First, a model-free adaptive control (MFAC) is designed based on data-driven ideology and a full-form dynamic linearization (FFDL) method is utilized to online estimate time-varying parameter pseudo gradient (PG) to establish an equivalent data model of AUV motion. Second, the iterative extended state observer (IESO) scheme is designed to combine with FFDL-MFAC. Because the proposed novel controller is able to learn from repeated iterations, the proposed novel controller can estimate and compensate the model approximation error produced by external environmental unknown disturbance. Third, three-dimensional motion is decoupled into horizontal and vertical and a multi closed-loop control structure is designed that exhibits faster convergence rate and reduces sensitivity to parameter jumps than single closed-loop system. Finally, two simulation scenarios are designed featuring non external disturbance and Gaussian noise of signal-to-noise ratio of 90 dB. The simulation results reveal the superiority of FFDL. Furthermore, we adpot the technical parameters data of T-SEA I AUV to conduct numerical simulation, aunderwater trajectory as the tracking scenario and set waves to 0.5 m and current to 0.2 m/s to simulate Lv.2 ocean conditions of "International Ocean State Standard". The simulation results demonstrate the effectiveness and robustness of the proposed tracking control algorithm.