自治水下机器人运动控制的动力学分析

运动控制是水下机器人自治化的核心,准确的动力学分析为分析控制系统的物理学特性提供了理论依据。以葛特勒为原始母型方程,深入分析了水下机器人在水下运动中的受力情况,建立了水下机器人水下运动的一般方程,为自治水下机器人控制系统的设计和仿真提供了调试环境。     

基于小脑模型关节控制器的水下机械手复合运动控制的研究及仿真

水下机械手系统是一个高度非线性强耦合的作业系统,作业环境非常复杂且受到强干扰.考虑水动力对水下机械手的作用,推导了水下机械手的动力学模型;提出了一种基于小脑模型关节控制器与PID的复合控制算法,使水下机械手具有在线学习能力,能适应复杂的水下作业环境.以二关节水下机械手为例,利用MATLAB/Simulink对水下机械手的作业控制进行了仿真研究,结果证明,该控制方法和动力学模型可以有效地用于水下机械手的控制研究.     

复合式驱动小型两栖机器人水下运动控制研究

针对两栖环境中机器人多自由度灵活稳定运动的需求,设计了一种具有"轮-腿-矢量喷水"复合驱动机制的小型两栖球形机器人。首先介绍了机器人的主要结构组成:一个密闭的上半球壳、两个可开关的1/4球壳、4条复合式驱动腿以及滑行模块等;其次,对球形机器人的复合驱动机制进行分析和建模;接着,根据水下环境和机器人的特性,设计了基于传统PID算法的神经网络自整定控制算法;最后,在室内水池中进行了机器人运动的实验测试。实验结果表明,机器人在水中运动性能良好,运动轨迹和姿态角误差在控制器接受范围之内。所提出的具有复合驱动机制的自主式两栖球形机器人,在滨海两栖环境的资源勘测等方面具有广阔的应用前景。     

核电站多功能水下打捞机器人系统研究

在核电站中,存在辐照剂量高、结构环境复杂等问题,操作人员作业时不可避免地会受到核辐射照射,对操作人员生命安全带来极大威胁。针对上述问题,研制出作业于核环境下的核电站多功能水下打捞机器人。首先,对机器人进行运动学分析,分别求解出机械手的正逆运动学方程及奇异位形;在此基础上,考虑水阻力、附加质量力以及浮力的影响,建立了机器人的水动力学模型,对机器人复杂水下动力学问题进行描述;最后,根据理论分析研制出该机器人第3代工程样机,并通过核电站现场实验对该机器人进行实验验证。实验结果表明,核电站多功能水下打捞机器人能够快速准确的完成异物抓取作业,实现核环境下的水下异物搜索与异物打捞的设计目标。     

基于遗传算法的自治水下机器人水动力参数辨识方法

针对传统确定自治水下机器人(Autonomous underwater vehicle,AUV)水动力参数试验和理论计算的困难性及以往辨识方法优化结果趋于局部最优解的缺点,提出一种基于遗传算法的AUV水动力参数辨识方法,该方法不受参数初值选取的影响,具有较好的鲁棒性和全局寻优特性,可为AUV运动控制、状态预报及控制系统开发等提供动力学模型。针对开架式AUV原型样机CRanger-01,在对其进行动力学建模分析的基础上,利用该方法对其水平面运动水动力参数进行辨识,得出了CRanger-01的19个水平面水动力参数,与实际值进行比较后,辨识误差在允许范围之内。通过运动仿真对模型进行验证,结果表明该算法能有效辨识AUV水动力参数,可为工程实践提供参考依据。     

水下机器人运动控制仿真研究

设计了一种水下机器人,它由防水基体、螺旋桨推进器和伺服电机组成。姿态传感器用于采集水下运动的姿态信息,通过单片机控制系统,采用PID算法调节螺旋桨推进器的角度,完成水下机器人的前进、后退、升降、转向等动作,采用Arduino微控制器平台对直流电机速度、伺服电机位置进行控制。仿真实验结果表明:该控制器可以有效地对直流电动机转速、伺服电机位置进行控制。     

水下捕捞机器人水动力学性能分析

海参捕捞机器人在水下捕捞作业时的性能受姿态变化的影响较大,为了使海参捕捞机器人始终保持最佳性能,需要在实际应用前对不同姿态下的捕捞机器人进行水动力学分析。利用计算流体力学软件 中的RNG 湍流模型作为仿真模型,考虑到仿真计算的精度,对近壁区域的处理进行了研究,在湍流模型的基础上加入了标准壁面函数。应用该模型对水下捕捞机器人水平直航、水平斜航和垂直斜航3种姿态下的水阻力和水阻力矩进行分析。结果表明:不同的姿态将影响水下捕捞机器人所受到的水阻力和水阻力矩的大小;在水平直航时捕捞机器人受到垂直向下的作用力较大,而产生的俯仰力矩较小;在水平斜航时漂角对捕捞机器人的影响较大;在垂直斜航时捕捞机器人的垂向力和俯仰力矩均随着流速和攻角的增大而增加。     

6自由度水下机器人动力学分析与运动控制

对6自由度水下机器人的动力学与运动控制进行研究。首先考虑重力、浮力、推力以及水动力的影响,建立水下机器人的动力学模型,对机器人的复杂水下动力学行为进行描述。在此基础上,根据解出加速度法设计非线性控制器,包括内外两个控制回路。其中外控制回路根据机器人实际轨迹与期望轨迹之间的偏差进行负反馈控制,内控制回路根据机器人动力学特性引入非线性补偿,把机器人转化为一个更易于控制的线性系统,从而准确实现对理论轨迹的跟踪。最后对水下机器人跟踪目标进行运动控制仿真。从仿真结果可以看出,利用该方法可以使水下机器人具有良好的轨迹跟踪能力。     

差压式管道机器人运动控制方法研究

为了提高管道内检测的精度与效率,研究了差压式管道机器人运动控制方法。针对当前差压式管道机器人机构设计中采用两端外套密封圈式清管器,由此导致速度难以控制的问题,按照驱动力与可控性指标设计了机器人的结构。在此基础上给出了差压式管道内检机器人动力学模型。对差压式管道机器人的运动控制进行了深入分析,给出了机器人与管壁取不同间隙条件下,机器人稳定运行速度与流体的流速之间的特性关系。根据分析结果设计了机器人的控制方案,给出了控制流程图,最后通过实验证明了所提方法的效果。     

水下装备挖掘过程的动力学研究

文中用多体动力学方法对海底机器人挖掘过程的动力学进行了研究.基于海底土壤特征建立了挖掘过程中工具-土壤之间相互作用的土动力学模型,利用莫里斯理论建立了铲斗等水阻力学模型,然后,将上述模型融合到整体挖掘动力学模型中,并采用机械动力学模拟软件ADAMS进行了仿真.     

Containment control of networked autonomous underwater vehicles: A predictor-based neural DSC design

This paper investigates the containment control problem of networked autonomous underwater vehicles in the presence of model uncertainty and unknown ocean disturbances. A predictor-based neural dynamic surface control design method is presented to develop the distributed adaptive containment controllers, under which the trajectories of follower vehicles nearly converge to the dynamic convex hull spanned by multiple reference trajectories over a directed network. Prediction errors, rather than tracking errors, are used to update the neural adaptation laws, which are independent of the tracking error dynamics, resulting in two time-scales to govern the entire system. The stability property of the closed-loop network is established via Lyapunov analysis, and transient property is quantified in terms of L₂ norms of the derivatives of neural weights, which are shown to be smaller than the classical neural dynamic surface control approach. Comparative studies are given to show the substantial improvements of the proposed new method.     

A path tracking control algorithm for underwater mining vehicles

In this paper, a path tracking control algorithm is formulated for the use of tracked underwater mining vehicles. The algorithm consists of two parts, the forward velocity control and the heading angle control. The control algorithm is designed based on kinematics, and it considers the track slips and the longitudinal and yaw dynamic models of the tracked vehicle including the soil-track interaction force model. The desired heading angle is obtained by the so-called “Line of Sight” method. The suggested algorithm is tested by numerical simulations using the TRACSIM software developed by MOERO/KORDI, Korea. After the control gains are tuned by a series of numerical simulations, the algorithm is verified on a scale vehicle on air on a soil bin test bed containing the cohesive soil of the Bentonite-water mixture. This paper was recommended for publication in revised form by Associate Editor Kyongsu Yi Sup Hong received the B.Sc. and the M.sc. degree in the department of naval architecture and ocean engineering from Seoul National University, Korea, and the Doctor of Engineering degree in mechanical engineering from the Technical university of Aachen, Germany. Currently, he is the principal researcher at MOERI (Maritime and Ocean Engineering Research Institute), Korea. His main research areas include dynamics of marine structure, and development of marine mineral resources. Especially, he is focusing on the development of deep seabed mining technologies since 1994. Mooncheol Won received the B.Sc. and the M.sc. degree in the department of naval architecture and ocean engineering from Seoul National University, Korea, and the Ph.D. degree in mechanical engineering from the University of California at Berkeley, USA. Currently, he is a professor in the department of mechatronics engineering of Chungnam national university, Korea. His research interests include control of maritime and mechatronics systems, and machine learning applications of robotic systems.     

Dynamic surface fault tolerant control for underwater remotely operated vehicles

In this paper, we present a two stages actuator Fault Tolerant Control (FTC) strategy for the trajectory tracking of a Remotely Operated Vehicle (ROV). Dynamic Surface Control (DSC) is used to generate the moment and forces required by the vehicle to perform the desired motion. In the second stage of the control system, a fault tolerant thruster allocation policy is employed to distribute moment and forces among the thrusters. Exhaustive simulations have been carried out in order to compare the performance of the proposed solution with respect to different control techniques (i.e., PID, backstepping and sliding mode approaches). Saturations, actuator dynamics, sensor noises and time discretization are considered, in fault-free and faulty conditions. Furthermore, in order to provide a fair and exhaustive comparison of the control techniques, the same meta-heuristic approach, namely Artificial Bee Colony algorithm (ABC), has been employed to tune the controllers parameters.     

Diving autopilot design for underwater vehicles using multi-objective control synthesis

This paper presents the mathematical modeling, guidance and robust control synthesis of a highly maneuverable submersible vehicle (or underwater vehicle) when performing a specific mission at shallow submergence conditions. First, the vertical plane motions (heave and pitch) of the vehicle are modeled by a set of maneuvering equations. After model simplification, a state-space model is compactly obtained. Then a state-feedback controller is proposed for the accurate depth-keeping and pitch motion controls of the vehicle. The control actions to the generalized plant can be provided by the mixedH ₂/H _∞ optimal synthesis as well as closed-loop pole constraint with LMIs. The feasibility of the guidance and control approach is verified with direct numerical simulations. The proposed approach ensures reasonable depth-keeping and minimal pitch motions, even under a given uncertainty condition.     

一种水下机器人混合模糊P+ID控制方法

针对具有非线性动力学特性的水下机器人的运动控制,提出采用解析式描述的单输入模糊控制器取代常规数字PID控制器中的比例项,并保持原有常规PID控制器的结构和参数不变,得到一种混合模糊P+ID控制方法.研究了水下机器人混合模糊P+ID控制的参数调节方法,并采用小增益定理分析了引入模糊控制后的系统输入输出稳定性.采用水下机器人的非线性动力学模型进行了仿真实验,结果表明提出的混合模糊P+ID控制具有比常规PID控制更好的性能.     

Cooperative path planning of multiple autonomous underwater vehicles operating in dynamic ocean environment

This paper presents a two-stage cooperative path planner for multiple autonomous underwater vehicles operating in dynamic environment. In case of static environment, global Legendre pseudospectral method is employed for collision-free paths of vehicles for the purpose of minimum time consumption and simultaneous arrival. Moreover, in order to keep the multiple autonomous underwater vehicles safe from collisions on the path segments connecting two adjacent control nodes, an adaptive intermediate knots insertion algorithm is introduced. In the on-line planning stage, the local re-planning strategy aims at avoiding collisions with unexpected dynamic obstacles by two consecutive avoidance maneuvers, and the differential flatness property of autonomous underwater vehicle is utilized, which can help the vehicles react fast enough to avoid moving obstacles.     

自治水下机器人自适应滑膜控制

对影响自治水下机器人控制性能的因素进行分析,提出将自适应滑模控制方法应用于水下机器人的深度控制,使其在在各种干扰的条件下仍保持稳定且具有满意的性能.采用系统辨识的方法得到系统的模型,进而通过辨识得到的模型修正滑膜控制量.引入平滑饱和函数,改善控制的暂态品质和震颤现象.仿真结果表明控制算法的有效性.     

水下滑翔机器人控制系统研究与开发

文章首先介绍了水下滑翔机器人的组成结构和工作原理,其次提出了水下滑翔机器人的控制系统方案,再次说明了控制系统软、硬件的设计与实现,最后完成了水下实验。实验结果证明控制系统设计合理,运行稳定,可以满足控制要求。     

Extended model predictive control scheme for smooth path following of autonomous vehicles

This paper presents an extended model predictive control (MPC) scheme for implementing optimal path following of autonomous vehicles, which has multiple constraints and an integrated model of vehicle and road dynamics. Road curvature and inclination factors are used in the construction of the vehicle dynamic model to describe its lateral and roll dynamics accurately. Sideslip, rollover, and vehicle envelopes are used as multiple constraints in the MPC controller formulation. Then, an extended MPC method solved by differential evolution optimization algorithm is proposed to realize optimal smooth path following based on driving path features. Finally, simulation and real experiments are carried out to evaluate the feasibility and the effectiveness of the extended MPC scheme. Results indicate that the proposed method can obtain the smooth transition to follow the optimal drivable path and satisfy the lateral dynamic stability and environmental constraints, which can improve the path following quality for better ride comfort and road availability of autonomous vehicles.     

自主挖掘机器人控制系统设计

挖掘机具备自动识别作业对象物,自行规划并控制执行单元完成作业任务的能力.通过实验验证,该自主挖掘机器人控制系统满足现场作业精度要求,可有效提高作业质量,减轻劳动强度,提高生产效率,为工程机械的智能化发展提供了有益的参考,具有重要的社会经济效益.