Model predictive and non-cooperative dynamic game fault recovery control strategies for a network of unmanned underwater vehicles

In this paper, the problem of control and fault recovery for a team of autonomous underwater vehicles in the presence of loss of effectiveness (LOE) actuator faults is addressed. Towards this end, two different fault recovery control strategies based on the model predictive control technique as well as the dynamic game theory are proposed and developed. Given the allowable information that can be exchanged among the agents, both centralised and semi-decentralised recovery control schemes are considered and their associated corresponding fault recovery strategies are developed. The proposed active fault recovery control strategies incorporate both the online inaccurate as well as delayed actuator fault estimates to reconfigure the nominal (healthy state) controllers. The effectiveness of the proposed semi-decentralised fault recovery control schemes is quantitatively investigated through extensive simulation case studies considering various LOE actuator fault severities in one or more unmanned vehicles as well as fault detection and isolation module imperfections such as fault estimation error and time delays in detecting the faults. The simulation results demonstrate and illustrate that our proposed semi-decentralised recovery control scheme can maintain acceptable degraded tracking and formation keeping performance of both the faulty and healthy agents in the team with lower computational and communication bandwidth requirements as well as lower or fairly close control effort cost as compared to the centralised control recovery scheme.     

Depth control of autonomous underwater vehicles using indirect robust control method

In this article, we propose a robust depth control design scheme for autonomous underwater vehicles (AUVs) in the presence of hydrodynamic parameter uncertainties and disturbances. The controller is designed via a new indirect robust control method that handles the uncertainties by formulating the uncertainty bounds into the cost functional and then transforming the robust control problem into an equivalent optimal control problem. Both robust asymptotic stability and optimality can be achieved and proved with this new formulation. The θ-D method is utilised to solve the resultant nonlinear optimal control problem such that an approximate closed-form feedback controller can be obtained and thus is easy to implement onboard without intensive computation load. Simulation results demonstrate that robust depth control is accomplished under the system parameter uncertainties and disturbances with small control fin deflection requirement.     

The bio-inspired model based hybrid sliding-mode tracking control for unmanned underwater vehicles

In this paper a novel hybrid control strategy is developed for trajectory tracking control of unmanned underwater vehicle (UUV). The proposed hybrid control strategy consists of two subsystems: a virtual velocity controller and a sliding-mode controller. The tracking errors are shown to asymptotically converge to zero by Lyapunov stability theory using the new approach, whereas in the traditional backstepping method, speed jump occurs if the tracking error changes suddenly. The biologically inspired model is designed to smooth the virtual velocity controller output, avoid speed jumps of underwater vehicles and satisfy the thruster control constraint. The effectiveness and efficiency of the proposed control strategy are demonstrated through simulations and comparison studies.     

Autonomous underwater vehicles: Hybrid control of mission and motion

This paper provides an experimental implementation and verification of a hybrid (mixed discrete state/ continuous state) controller for semi-autonomous and autonomous underwater vehicles in which the missions imply multiple task robot behavior. An overview of some of the missions being considered for this rapidly developing technology is mentioned including environmental monitoring, underwater inspection, geological survey as well as military missions in mine countermeasures.The functionalities required of such vehicles and their relation to intelligent control technology is discussed. In particular, the use of Prolog as a computer language for the specification of the discrete event system (DES) aspects of the mission control is proposed. The connections between a Prolog specification and the more common Petri Net graphical representation of a DES are made. Links are made between activation commands, transitioning signals, and the continuous state dynamic control system (DCS) responsible for vehicle stabilization.Details are given of the NPS Phoenix vehicle implementation at the present time, together with experimental validation of the concepts outlined using a simplified example mission. The paper ends with a listing of questions and concerns for the evaluation of software controllers. A list of references is given for readers interested in this subject.     

Do whatever works: A robust approach to fault-tolerant autonomous control

This paper describes a highly distributed fault-tolerant control system capable of compensating for deficiencies in system-level performance even when the cause of a fault cannot be explicitly identified. Developed for an autonomous underwater vehicle that must remain operational for several weeks without human intervention, this system must be capable of dealing with events that cannot be anticipated at design time. A unique aspect of this system is that it handles such events by attempting to do whatever works if it is unable to diagnose and correct specific faults. The software architecture used in this approach is applicable to a wide range of complex autonomous control applications.     

Switched seesaw control for the stabilization of underactuated vehicles

This paper addresses the stabilization of a class of nonlinear systems in the presence of disturbances, using switching controllers. To this effect we introduce two new classes of switched systems and provide conditions under which they are input-to-state practically stable (ISpS). By exploiting these results, a methodology for control systems design—called switched seesaw control—is obtained that allows for the development of nonlinear control laws yielding input-to-state stability. The range of applicability and the efficacy of the methodology proposed are illustrated via two nontrivial design examples. Namely, stabilization of the extended nonholonomic double integrator (ENDI) and stabilization of an underactuated autonomous underwater vehicle (AUV) in the presence of input disturbances and measurement noise.     

Robust control of variable speed autonomous underwater vehicle

Set point tracking control of autonomous underwater vehicle (AUV) via robust model predictive control (RMPC) is considered. Input-constrained RMPC with integral action, which has been developed in our previous work, is used to control the AUV in this study. In order to derive a RMPC control rule, non-linear dynamics of AUV with six degree of freedom is linearized at certain operating points. So, horizontal and vertical plane dynamics of system are represented by linear models which have polytopic uncertainties. Since the derived control rule will be used in real time, the computation time should be reduced. To overcome this computational time problem and get rid of trial–error step of Algorithm 1, a new algorithm is proposed here. The simulations are carried out using the control rule based on this algorithm and these results are presented.     

一种水下机器人传感器故障诊断与容错控制方法

采用自适应滤波器ＦＩＲ 对水下机器人进行在线自适应建模,并利用ＬＭＳ算法来调节滤波器的权系数．通过对滤波器权系数和误差信号平方的分析,实时检测出传感器的故障,并应用ＦＩＲ 滤波器输出替代故障传感器信号,实现传感器故障情形下水下机器人容错控制．应用该方法对Ｏｕｔｌａｎｄ１０００水下机器人传感器的故障进行检测和容错,实验结果表明所提故障检测方法准确可靠,具有较好的容错效果．     

采用一致性算法与虚拟结构的多自主水下航行器编队控制

采用一致性算法与虚拟结构法研究了多自主水下航行器(AUV)小尺度编队控制问题.首先针对各自主水下航行器拥有不同虚拟领航者信息(参考信息)的情况,通过对各AUV拥有的不一致参考信息进行一致性协商而达到状态一致.其次,基于虚拟结构思想采用坐标变换将各AUV相对于虚拟领航者的相对位置转换为各自的期望位置,并设计了一种有限时间跟踪控制律以确保各AUV能在有限时间内跟踪上其期望轨迹,从而实现了多AUV的小尺度有限时间编队控制.最后仿真实验验证了控制策略的有效性.     

Multimodal control of sensors on multiple simulated unmanned vehicles

The use of multimodal (speech plus manual) control of the sensors on combinations of one, two, three or five simulated unmanned vehicles (UVs) is explored. Novice controllers of simulated UVs complete a series of target checking tasks. Two experiments compare speech and gamepad control for one, two, three or five UVs in a simulated environment. Increasing the number of UVs has an impact on subjective rating of workload (measured by NASA-Task Load Index), particularly when moving from one to three UVs. Objective measures of performance showed that the participants tended to issue fewer commands as the number of vehicles increased (when using the gamepad control), but, while performance with a single UV was superior to that of multiple UVs, there was little difference across two, three or five UVs. Participants with low spatial ability (measured by the Object Perspectives Test) showed an increase in time to respond to warnings when controlling five UVs. Combining speech with gamepad control of sensors on UVs leads to superior performance on a secondary (respond-to-warnings) task (implying a reduction in demand) and use of fewer commands on primary (move-sensors and classify-target) tasks (implying more efficient operation).

Statement of Relevance: Benefits of multimodal control for unmanned vehicles are demonstrated. When controlling sensors on multiple UVs, participants with low spatial orientation scores have problems. It is proposed that the findings of these studies have implications for selection of UV operators and suggests that future UV workstations could benefit from multimodal control.     

Synchronization of multiple autonomous underwater vehicles without velocity measurements

In this paper,we investigate the synchronization control of multiple autonomous underwater vehicles (AUVs),considering both state feedback and output feedback cases.Treating multiple AUVs as a graph,we define the tracking error of each AUV with both its own tracking error and the relative position errors with respect to its neighbors taken into account.Lyapunov analysis is used to derive the control law for each AUV.For the output feedback case,a passive filter is used to compensate for the unknown relative velocity errors among AUVs,and an observer is employed to estimate the velocity of the AUV itself.Rigid mathematical proof is provided for the proposed algorithms for both state feedback and output feedback cases.Simulations are provided to demonstrate the effectiveness of the proposed approach.It is shown that,the synchronization error is smaller in the case of considering the relative errors between AUVs than in the case of considering the tracking error of the single AUV only.     

Case-based path planning for autonomous underwater vehicles

Case-based reasoning is reasoning based on specific instances of past experience. A new solution is generated by retrieving and adapting an old one which approximately matches the current situation. In this paper, we outline a case-based reasoning scheme for path planning in autonomous underwater vehicle (AUV) missions. An annotated map database is employed to model the navigational environment. Routes which are used in earlier missions are represented as objects in the map. When a new route is to be planned, the path planner retrieves a matching route from the database and modifies it to suit to the current situation. Whenever a matching route is not available, a new route is synthesized based on past cases that describe similar navigational environments. Case-based approach is thus used not only to adapt old routes but also to synthesize new ones. Since the proposed scheme is centered around reuse of old routes, it would be fast especially when long routes need to be generated. Moreover, better reliability of paths can be expected as they are adapted from earlier missions. The scheme is novel and appropriate for AUV mission scenarios. In this paper, we describe the representation of navigation environment including past routes and objects in the navigational space. Further, we discuss the retrieval and repair strategies and the scheme for synthesizing new routes. Sample results of both synthesis and reuse of routes and system performance analysis are also presented. One major advantage of this system is the facility to enrich the map database with new routes as they are generated.This work was supported in part by National Science Foundation Grant No. BCS-9017990.     

Simulation program complex for studying motion control methods for autonomous underwater vehicles

Development of a graphical simulation complex for studying motion control methods for autonomous underwater vehicles is discussed. Its structure and functioning scheme are presented. An approach to solving navigation problem and to 3D reconstruction of underwater environment from a given sequence of digital images is described. It is based on the use of an extended Kalman filter and original algorithm of dense 3D recovery of the environment points. Results of computational experiments and estimates of the efficiency of the approach are presented.     

Experiments in the coordinated control of an underwater arm/vehicle system

The addition of manipulators to small autonomous underwater vehicles (AUVs) can pose significant control challenges due to hydrodynamic interactions between the arm and the vehicle. Experiments conducted at the Monterey Bay Aquarium Research Institute (MBARI) using the OTTER vehicle have shown that dynamical interactions between an arm and a vehicle can be very significant. For the experiments reported in this paper, a single-link arm was mounted on OTTER. Tests showed that for 90-degree, two-second repetitive slews of the arm, the vehicle would move as much as 18 degrees in roll and 14 degrees in yaw when no vehicle control was applied.Using a new, highly accurate model of the arm/vehicle hydrodynamic interaction forces, which was developed as part of this research, a coordinated arm/vehicle control strategy was implemented. Under this model-based approach, interaction forces acting on the vehicle due to arm motion were predicted and fed into the vehicle controller. Using this method, station-keeping capability was greatly enhanced. Errors at the manipulator end point were reduced by over a factor of six when compared to results when no control was applied to the vehicle and by a factor of 2.5 when compared to results from a standard independent arm and vehicle feedback control approach. Using the coordinated-control strategy, arm end-point settling times were reduced by a factor three when compared to those obtained with arm and vehicle feedback control alone. These dramatic performance improvements were obtained with only a five-percent increase in total applied thrust.     

Problems of creating intelligent autonomous robotic underwater vehicles and their application

Basic scientific and applied tasks to be accomplished by autonomous robotic underwater vehicles are considered, and distinctive features of their control system are analyzed. Some unsolved fundamental problems in this subject are formulated. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 100–110, September–October 2007.     

Autonomous underwater vehicles for scientific and naval operations

Recognizing the potential of autonomous underwater vehicles for scientific and military applications, in 1997 MIT and the NATO Undersea Research Centre initiated a Joint Research Project (GOATS), for the development of environmentally adaptive robotic technology applicable to mine counter measures (MCM) and rapid environmental assessment (REA) in coastal environments. The August 2001 GOATS Conference marked the end of this 5 years project, but did not mark the end of the work. The Centre initiated in 2002 a new long-term programme to explore and demonstrate the operational benefits and performances of AUV for covert preparation of the battlespace. Recently the work addressed the evaluation of commercial off-the-shelf (COTS) AUV technology for MCM operations in response to terrorist mining of port. The paper summarizes the work performed and refers to the scientific publications derived from the AUV programme at the NATO Undersea Research Centre.     

A waypoint-tracking controller for a bionic autonomous underwater vehicle with two pectoral fins

This study aims to develop a waypoint-tracking control system for a biomimetic underwater vehicle (BUV). The BUV is propelled by wide paired pectoral foils, and each pectoral foil is driven by three independent fin rays. To simplify the control strategy, the maximum flapping amplitude of the pectoral fin is used to control the forward velocity, and a turning factor is defined for the manoeuvre control. Several swimming experiments are carried out to investigate the influence of the control parameters on the swimming performance of the prototype. Based on the results of the swimming experiments, a waypoint-tracking control system is proposed, which contains two layers: the velocity control layer and the heading angle control layer. A subdivision control method is adopted by the velocity control layer to get the maximum flapping amplitude. The fuzzy control method is employed by the heading angle control layer to obtain the turning factor for steering motion. Several waypoint-tracking experiments are carried out to verify effectiveness of the control system. The results show that the prototype can automatically reach the target area with the designed control system, even though the waypoints are arranged or randomly given.     

Optimal thrusters steering for dynamically reconfigurable underwater vehicles

When using a Remotely Operated Vehicle (ROV), on-the-fly reconfiguration of the thrusters orientations allows to adjust its propulsion and manoeuvrability capabilities according to the mission progress. To optimise the actuation, the interaction between thrusters due to cross-flows is modelled and included in the thrust related objective function to be maximised. Run-time effective solutions use a sparse look-up table to initialise a fast direct-search local optimisation algorithm. The found thrusters steering configurations show higher thrust gains compared with the traditional fixed ‘vectored’ configuration of currently available ROVs.     

Experimental study on a learning control system with bound estimation for underwater robots

Underwater robotic vehicles (URVs) have become an important tool for numerous underwater tasks due to their greater speed, endurance, depth capability, and a higher factor of safety than human divers. However, most vehicle control system designs are based on simplified vehicle models and often result in poor vehicle performance due to the nonlinear and time-varying vehicle dynamics having parameter uncertainties. Conventional proportional-integral-derivative (PID) type controllers cannot provide good performance without fine-tuning the controller gains and may fail for sudden changes in the vehicle dynamics and its environment. Conventional adaptive control systems based on parameter adaptation techniques also fail in the presence of unmodeled dynamics.This paper describes a new vehicle control system using the bound estimation techniques, capable of learning, and adapting to changes in the vehicle dynamics and parameters. The control system was extensively wet-tested on the Omni-Directional Intelligent Navigator (ODIN)-a six degree-of-freedom, experimental underwater vehicle developed at the Autonomous Systems Laboratory, and its performance was compared with the performance of a conventional linear control system. The results showed the controller's ability to provide good performance in the presence of unpredictable changes in the vehicle dynamics and its environment, and it's capabilities of learning and adapting.