Robust leader-follower formation tracking control of multiple underactuated surface vessels

This paper is concerned with the formation control problem of multiple underactuated surface vessels moving in a leader-follower formation.The formation is achieved by the follower to track a virtual target defined relative to the leader.A robust adaptive target tracking law is proposed by using neural network and backstepping techniques.The advantage of the proposed control scheme is that the uncertain nonlinear dynamics caused by Coriolis/centripetal forces,nonlinear damping,unmodeled hydrodynamics and disturbances from the environment can be compensated by on line learning.Based on Lyapunov analysis,the proposed controller guarantees the tracking errors converge to a small neighborhood of the origin.Simulation results demonstrate the effectiveness of the control strategy.     

自主水下航行器的软变结构控制

研究自主水下航行器系统的软变结构控制策略问题。首先分析软变结构控制系统的结构特征,利用双曲正切函数,给出控制受限情形的软变结构控制策略。其次利用Lyapunov稳定性理论,讨论自主水下航行器软变结构控制系统的稳定性,然后构造了基于双曲正切函数的软变结构控制器,给出自主水下航行器软变结构控制的具体算法。基于双曲正切函数的自主水下航行器软变结构控制系统调节精度高,响应速度快,有效地削弱了系统抖振。最后通过一个仿真实验,比较了自主水下航行器垂直深度通道的4种控制策略对系统性能的影响,从而验证了研究方法的有效性。     

Tracking control for underwater vehicle-manipulator systems withvelocity estimation

In this paper, the problem of tracking a desired motion trajectory for an underwater vehicle-manipulator system without using direct velocity feedback is addressed. For this purpose, an observer is adopted to provide estimation of the system's velocity needed by a tracking control law. The combined controller-observer scheme is designed so as to achieve exponential convergence to zero of both motion tracking and estimation errors. In order to avoid representation singularities of the orientation, unit quaternions are used to express the vehicle attitude. Implementation issues are also considered and simplified control laws are suggested, aimed at suitably trading off tracking performance against reduced computational load. Simulation case studies are carried out to show the effectiveness of the proposed controller-observer algorithm. The obtained performance is compared to that achieved with a control scheme in which the velocity is reconstructed via numerical differentiation of position measurements. The results confirm that the chattering on the control commands is significantly reduced when the controller-observer strategy is adopted in lieu of raw numerical differentiation; this leads to lower energy consumption at the actuators and increases their lifetime     

端口受控哈密顿方法的电力双推进无人船航向航速控制

以电力双推进无人船航速航向控制为主要研究问题,使用永磁同步电机作为无人船螺旋桨的驱动电机,采用基于端口受控哈密顿(PCH)方法,有效的降低了系统损耗,使无人船驱动系统输出功率得到了优化。仿真结果表明,系统能较快达到稳定状态,实现了无人船的速度控制要求,提升了无人船系统的续航能力。     

经济发展影响下我国海洋环境污染压力变化趋势及污染减排对策分析

对20世纪90年代以来我国经济发展影响下的海洋环境污染变化趋势进行了分析,指出近年来我国海洋环境污染防治工作取得了一定成效,但近岸海域污染的总体形势依然严峻,并可能随着经济总量的增长而再次恶化,氮磷营养盐超标导致的海水富营养化是近岸海域的主要污染问题。讨论了我国现行的污染物减排策略对海洋污染防治的局限性,并以国家"十二五"发展规划、沿海区域社会经济发展规划为依据,综合分析"十二五"期间我国海洋环境污染防治面临的压力和主要入海污染源的排污特征,建议应对农业非点源开展源头污染控制、对沿海地区点源加强末端治理,实施流域-河口-海域联动的入海污染物减排策略。     

Layered berthing method and experiment of unmanned surface vehicle based on multiple constraints analysis

Considering the dynamic changes of unmanned surface vehicle (USV) in berthing tasks, the planning and control modes are divided into two phases: the remote phase and the terminal phase. According to the main influencing factors of the two phases, an improved artificial potential field method is proposed to complete autonomous berthing trajectory planning based on the analysis of environment constraint, berth point constraint and USV’s dynamics constraint. Combining with the dynamic characteristics and control objectives at different phases of berthing and analyzing the fuzzy rule regulation strategy of USV’s heading and speed control, an improved adaptive fuzzy PID control method is proposed to solve the control problem of USV, which is influenced by weak maneuver, large disturbance, limited water area and strong shore effect. Finally, the comparative test of berthing simulation verifies the superiority of the proposed control method. The autonomous berthing field experiment is completed based on the "Dolphin-I" small USV. It verifies the validity and feasibility of the proposed autonomous berthing method.     

Adaptive sliding mode control of autonomous underwater vehicles inthe dive plane

The problem of controlling an autonomous underwater vehicle (AUV) in a diving maneuver is addressed. Having a simple controller which performs satisfactorily in the presence of dynamical uncertainties calls for a design using the sliding mode approach, based on a dominant linear model and bounds on the nonlinear perturbations of the dynamics. Nonadaptive and adaptive techniques are considered, leading to the design of robust controllers that can adjust to changing dynamics and operating conditions. The problem of using the observed state in the control design is addressed, leading to a sliding mode control system based on input-output signals in terms of drive-phase command and depth measurement. Numerical simulations using a full set of nonlinear equations of motion show the effectiveness of the proposed techniques     

Biomimetic reduction of wake deficit using tail articulation at low Reynolds number

The field of biomimetics seeks to distill biological principles from nature and implement them in engineering systems in an effort to improve various performance metrics. In this paper, a biology-based approach is used to address the problem of radiated propulsor noise in underwater vehicles using active control. This approach is one of "tail articulation" of a stator blade, which is carried out using a suitable strategy that effectively alters the flow field impinging on a rotor downstream and in turn changes the radiated noise characteristics of the rotor blades. A reduced-order two-dimensional noise model is developed by characterizing the impact of the articulation as a point circulation input, which is then used to develop an active control strategy. An experimental investigation of such a control strategy is also carried out in this paper using a simple benchtop open-channel water tunnel at Re=4000 and stepper motor controlled articulation. Tail articulations using sinusoidal and transient motion were able to reduce the wake deficit behind the stator by as much as 40-60%. The implications of the proposed method for reducing blade tonal noise in autonomous underwater vehicles are briefly discussed at the end of the paper.     

An Adaptive Single Neural Control for Variable Step-Size P&O MPPT of Marine Current Turbine System

Marine current energy has been increasingly used because of its predictable higher power potential. Owing to the external disturbances of various flow velocity and the high nonlinear effects on the marine current turbine (MCT) system, the nonlinear controllers which rely on precise mathematical models show poor performance under a high level of parameters’ uncertainties. This paper proposes an adaptive single neural control (ASNC) strategy for variable step-size perturb and observe (P&O) maximum power point tracking (MPPT) control. Firstly, to automatically update the neuron weights of SNC for the nonlinear systems, an adaptive mechanism is proposed to adaptively adjust the weighting and learning coefficients. Secondly, aiming to generate the exact reference speed for ASNC to extract the maximum power, a variable step-size law based on speed increment is designed to strike a balance between tracking speed and accuracy of P&O MPPT. The robust stability of the MCT control system is guaranteed by the Lyapunov theorem. Comparative simulation results show that this strategy has favorable adaptive performance under variable velocity conditions, and the MCT system operates at maximum power point steadily.

     

Multi-Behavior Fusion Based Potential Field Method for Path Planning of Unmanned Surface Vessel

The problem of the unmanned surface vessel(USV) path planning in static and dynamic obstacle environments is addressed in this paper. Multi-behavior fusion based potential field method is proposed, which contains three behaviors: goal-seeking, boundary-memory following and dynamic-obstacle avoidance. Then, different activation conditions are designed to determine the current behavior. Meanwhile, information on the positions, velocities and the equation of motion for obstacles are detected and calculated by sensor data. Besides, memory information is introduced into the boundary following behavior to enhance cognition capability for the obstacles, and avoid local minima problem caused by the potential field method. Finally, the results of theoretical analysis and simulation show that the collision-free path can be generated for USV within different obstacle environments, and further validated the performance and effectiveness of the presented strategy.     

Optimal measurement strategies for target tracking by a biomimetic underwater vehicle

This study presents a novel navigation and control system allowing a biomimetic-autonomous underwater vehicle (BAUV) to track a target. A Bayesian approach using an extended Kalman filter and combined localization and environmental mapping by a BAUV are implemented. This strategy selects the best sensor measurement by choosing one of several forward-looking directions. The body of the BAUV moves in a cyclical pattern; thus, an inexpensive echo sounder can be installed on the BAUV head to detect environmental features without the need for expensive scanning devices. The localization and environmental mapping problem is then transformed into a non-linear two-point boundary value problem. Optimal policies are to maintain the accuracy of predicted states and to approach minimal observation cost by solving the control problem. A line-of-sight guidance law is utilized that drives the BAUV to the target. An approach that controls the motion of the body/caudal fin and pectoral fins of the BAUV is utilized for target tracking. Estimation, measurement, and control processes are integrated to form a working system. Experiments using a test bed BAUV confirm the effectiveness of the proposed approach.     

A task-based hierarchical control strategy for autonomous motion of an unmanned surface vehicle swarm

In this paper, a hierarchical control framework with relevant algorithms is proposed to achieve autonomous navigation for an underactuated unmanned surface vehicle (USV) swarm. In order to implement automatic target tracking, obstacle avoidance and avoid collisions between group members, the control framework is divided into three layers based on task assignments: flocking strategy design, motion planning and control input design. The flocking strategy design transmits some basic orders to swarm members. Motion planning applies the potential function method and then improves it; thus, the issue of autonomous control is transformed into one of designing the velocity vector. In the last layer, the control inputs (surge force and yaw moment) are designed using the sliding mode method, and the problem of underactuation is handled synchronously. The proposed closed-loop controller is shown to be semi-asymptotically stable by applying Lyapunov stability theory, and the effectiveness of the proposed methodology is demonstrated via numeric simulations of a homogeneous USV swarm.     

大深度载人潜水器低速大漂角模糊滑模航向控制研究

通过模型试验测量大深度载人潜水器低速大漂角运动时所受到的非线性水动力。基于一种新的模糊滑模控制策略,为潜水器设计了鲁棒航向控制器。在不同的漂角子区间内分别设计局部镇定的滑模控制器,然后通过Takagi-Sugeno模糊推理系统将它们光滑连接,得到模糊滑模控制。仿真计算结果充分显示了该控制策略的有效性。     

船体结构腐蚀检测规划的成本及效益分析

建立了基于风险的船体结构腐蚀优化检测规划的成本-效益分析模型。以费效比作为选择最优检测策略的标准,最优的检测策略是在保证结构设计工作寿命期内的可靠指标大于最低可靠指标的基础上,使得结构生命周期内总的费效比最大。在此基础上,以受点腐蚀损伤的船体构件为例,对其检测策略进行了成本-效益评估,并对计算结果进行了敏感性分析。结果表明,基于风险的成本及效益分析方法可以将检测规划的经济性和可靠性有效地结合起来,能够在风险与成本之间达到一种平衡,它在优化检测策略时是有效的。     

Application of a proportional-integral control for the estimation of static formation temperatures in oil wells

A strategy based on proportional-integral (PI) feedback control was applied to solve an inverse heat transfer problem for estimating static formation temperatures (SFTs) from logged temperatures in oil wells. The PI control feedbacks the error between logged and simulated temperatures during the shut-in time process, existing SFT proposal. Thus, mathematically speaking an inverse heat transfer problem was solved in this way, since SFT represents the initial conditions (which are unknown) to solve the partial differential equations governing the heat transfer process in the wellbore-formation system. The mathematical model considers transient convective heat transfer due to circulation losses to the rock surrounding a well. The methodology was tested analyzing two oil wells (MB-3007 and MB-3009) from the Gulf of Mexico and results were compared against two classic methods. The method presented in this work needs only one temperature measurement for each fixed depth to estimate the SFT.     

基于强化学习的锚泊辅助动力定位系统智能决策研究

针对半潜平台锚泊辅助动力定位系统的最优定位点问题,设计了基于强化学习中深度神经网络的Q学习(DQN)控制策略的锚泊辅助动力定位的智能决策系统。该决策系统中DQN方法与比例—积分—微分(PID)控制方法相结合使用,实现系统优化。在基于机器人操作系统(ROS)平台的动力定位时域模拟程序中进行数值仿真,仿真结果验证了该系统在定位点决策问题上的可靠性和有效性,从而使半潜平台在面对未知海况时,均能寻找到最优定位点,在保证锚泊辅助动力定位系统可靠性的同时降低功率消耗,提高经济性。     

基于模糊PID的深海采矿机器人路径跟踪控制

深海采矿作业中,由于海底软泥稀软,采矿机器人极易打滑,以及海底地形、海流等干扰,采矿机器人容易偏离预定路径。针对采矿机器人的海底作业过程中路径跟踪问题,设计并分析了深海采矿机器人的路径跟踪控制系统。首先提出了艏向控制实现采矿机器人路径跟踪的控制算法,通过采矿机器人与当前目标点相对位置计算采矿机器人的目标艏向角,后基于运动学模型建立模糊比例积分微分(PID)的控制方法控制采矿机器人两侧转速差值进而控制采矿机器人艏向,从而使机器人按目标路径行走;同时为了防止输入过大引起打滑,基于动力学模型数值分析了采矿机器人主动轮角加速度与打滑率之间的关系,采取限制主动轮角加速度方式防止采矿机器人过度打滑;最后通过Matlab/Simulink建立系统模型对系统进行仿真分析。仿真结果表明,该控制算法能够良好地完成采矿机器人的路径跟踪任务。     

Adaptive output feedback control based on DRFNN for AUV

The tracking control problem of AUV in six degrees-of-freedom (DOF) is addressed in this paper. In general, the velocities of the vehicles are very difficult to be accurately measured, which causes full state feedback scheme to be not feasible. Hence, an adaptive output feedback controller based on dynamic recurrent fuzzy neural network (DRFNN) is proposed, in which the location information is only needed for controller design. The DRFNN is used to online estimate the dynamic uncertain nonlinear mapping. Compared to the conventional neural network, DRFNN can clearly improve the tracking performance of AUV due to its less inputs and stronger memory features. The restricting condition for the estimation of the external disturbances and network's approximation errors, which is often given in the existing literatures, is broken in this paper. The stability analysis is given by Lyapunov theorem. Simulations illustrate the effectiveness of the proposed control scheme.     

A Cascade Approach for Global Trajectory Tracking Control of Underactuated AUVs

A global trajectory tracking controller is presented for underactuated AUVs with only surge force and yaw moment in the horizontal plane. A transformation is introduced to represent the tracking error system into a cascade form. The global and uniform asymptotic stabilization problem of the resulting cascade system is reduced to the stabilization problem of two subsystems by use of the cascade approach. For the stabilization of the subsystem involving the yaw moment, a control law is proposed based on the feedback linearization method. Another subsystem is stabilized by designing a fuzzy sliding mode controller which can offer a systematical means of constructing a set of shrinking-span and dilating-span membership functions. In order to demonstrate the practicability of the proposed controller, control constraints, parameter uncertainties, and external disturbances are considered according to practical situation of AUVs. Simulation results show very good tracking performance and robustness of the proposed control schemes.     

Adaptive Neural Network Control with Control Allocation for A Manned Submersible in Deep Sea

This paper thoroughly studies a control system with control allocation for a manned submersible in deep sea being developed in China.The proposed control system consists of a neural-network-based direct adaptive controller and a dynamic control allocation module.A control energy cost function is used as the optimization criteria of the control allocation module,and weighted pseudo-inverse is used to find the solution of the control allocation problem.In the presence of bounded unknown disturbance and neural networks approximation error,stability of the closed-loop control system of manned submersible is proved with Lyaponov theory.The feasibility and validity of the proposed control system is further verified through experiments conducted on a semi-physical simulation platform for the manned submersible in deep sea.