共查询到19条相似文献，搜索用时 93 毫秒
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水下机器人避碰控制是自主作业的重要基础,但复杂的约束条件和模型的不精确性增加了避障路径跟踪的技术难度。在传统模型预测控制的基础上,结合作业场景多种约束条件,引入径向基函数神经网络,提出了一种水平面避碰控制方法。首先,采用径向基神经网络建立误差补偿函数,提高传统动力学预测模型精度;然后,结合避碰路径跟踪控制,在滚动优化环节选取性能指标函数,并显式引入障碍物、执行机构与控制稳定性等约束条件;最后,通过仿真试验证明该方法能够控制水下机器人跟踪避碰路径实现水平面内障碍物规避。 相似文献
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以7 000 m载人潜水器的工程需求为背景,以水下单目摄像机为视觉传感器,进行了水下机器人动力定位方法研究。该动力定位方法利用视觉系统测量得到水下机器人与被观察目标之间的三维位姿关系,通过路径规划、位置控制和姿态控制分解,逐步使机器人由初始位姿逼近期望位姿并最终定位于期望位姿,从而实现了机器人的4自由度动力定位。通过水池实验验证了提出的动力定位方法,并且机器人能够抵抗恒定水流干扰和人工位置扰动。同时,该动力定位方法还可以实现机器人对被观察目标的自动跟踪。 相似文献
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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。 相似文献
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以欠驱动自主水下机器人(Autonomous Underwater Vehicle,AUV)为试验平台,提出了一种水平面动力定位控制方法。根据自研 AUV 平台的运动执行机构配置,针对其欠驱动特性设计运动控制器,控制纵向推力与转艏力矩,经过路径跟踪与区域镇定两个阶段,使航行器先沿预设路径快速接近目标点,再低速逐渐调整水平位置,最终在该点附近小范围内保持悬停。结合试验数据证明：航行器可抵达并稳定在目标点附近 2 m 范围内,并且在受到外力扰动偏离后能够重新返回,从而验证该动力定位控制方法的有效性。 相似文献
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GDROV是用于堤坝探测的水下机器人,设计上属于开架式机器人,其精确的数学模型很难获得.采用基于模糊逻辑的直接自适应控制方法,利用模糊基函数网络逼近理想控制输出,通过模糊逻辑动态调整控制器的参数自适应律,可有效解决水下机器人控制问题.建立GDROV的水动力模型,给出基于模糊逻辑的直接自适应控制算法,最后通过仿真试验和外场试验验证了该控制器对模型的不确定性具有较强的鲁棒性,且具有良好的跟踪性能. 相似文献
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《海洋技术学报》2021,(4)
为获取高升力系数和升阻比的舵翼外形特征参数,本文以某型水下机器人舵翼为研究对象,将其表征量简化为展弦比、梢根比、前缘后掠角、攻角和剖面翼型5个设计参数。采用计算流体力学方法(CFD)模拟了流速为2 kn时,平板翼型厚度为6 mm的常见平面形状舵翼在不同来流下的流场情况,得到舵翼平面形状参数与其水动力性能和铰链力矩之间的变化规律和相对灵敏度,并对基于径向基函数模型(RBF)的优化结果进行分析,随后对比了不同剖面翼型对舵翼性能的影响。研究结果表明:攻角为6°左右时,舵翼可获得最佳水动力性能;剖面翼型对舵翼的水动力性能有较大影响,NACA00xx系列翼型可以显著提升舵翼的升阻比,并且翼型厚度越小,性能越佳;舵翼面积一定的条件下,后掠形舵翼具有优良的水动力性能,但铰链力矩较大;攻角较小时,梯形舵翼表现出较好的水动力性能,铰链力矩很小;攻角较大时,切尖三角形舵翼水动力性能与后掠舵翼基本持平,铰链力矩适中。 相似文献
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船载低频多波束测深声纳、侧扫声纳可以对深海海底地形地貌进行快速、高效、大面积探测,但其测量精度有限,难以满足深海科学考察、资源勘探开发对高精度海底地形地貌的需求。随着各类大深度水下移动载体(如深海拖体、水下机器人、遥控潜器和载人潜水器)的涌现,特别是各类耐高压测绘声纳的商业化,使大深度近海底精细地形地貌探测成为可能。首先分析了多波束测深声纳、侧扫声纳和测深侧扫声纳等3种测绘声纳的基本原理,然后分别介绍了各类测绘声纳的国内外典型商业化产品,并通过典型实例分析了其在大深度近海底精细测绘中的应用情况。 相似文献
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Depth-trim mapping control of underwater vehicle with fins 总被引：1，自引：1，他引：0
Underwater vehicle plays an important role in ocean engineering.Depth control by fin is one of the difficulties for underwater vehicle in motion control.Depth control is indirect due to the freedom coupling between trim and axial motion.It includes the method of dynamic analysis and lift-resistance-coefficient experiment and theory algorithm.By considering the current speed and depth deviation,comprehensive interpretation is used in object-planning instruction.Expected depth is transformed into expected trim.Dynamic output fluctuation can be avoided,which is caused by linear mapping of deviation.It is steady and accurate for the motion of controlled underwater vehicles.The feasibility and efficiency of the control method are testified in the pool and natural area for experiments. 相似文献
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The aim of this study is to solve the problem of poor tracking in autonomous underwater vehicle (AUVs) that are operating based on traditional line-of-sight (LOS) method when tracking different paths in a complex marine environment. An adaptive-LOS (ALOS) guidance law with drift angle compensation is proposed, and is employed to calculate the AUV’s desired course (direction of velocity) and heading. First, an appropriate look-ahead distance is derived by the ALOS guidance law in consideration of the predefined path curvature, real-time tracking error and speed of the AUV. Subsequently, proper compensation is provided with respect to the actual drift angle. Compared with traditional LOS operation, this method flexibly adjusts to a suitable look-ahead distance while considering many related factors, providing a better path following performance. Both simulation and experimental results are presented to validate the effectiveness of this method. 相似文献
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《Oceanic Engineering, IEEE Journal of》2008,33(2):69-88
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This paper is concerned with the robust control synthesis of autonomous underwater vehicle(AUV) for general path following maneuvers.First,we present maneuvering kinematics and vehicle dynamics in a unified framework.Based on H∞ loop-shaping procedure,the 2-DOF autopilot controller has been presented to enhance stability and path tracking.By use of model reduction,the high-order control system is reduced to one with reasonable order,and further the scaled low-order controller has been analyzed in both the frequency and the time domains.Finally,it is shown that the autopilot control system provides robust performance and stability against prescribed levels of uncertainty. 相似文献
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A randomized kinodynamic path planning algorithm based on the incremental sampling-based method is proposed here as the state-of-the-art in this field applicable in an autonomous underwater vehicle. Designing a feasible path for this vehicle from an initial position and velocity to a target position and velocity in three-dimensional spaces by considering the kinematic constraints such as obstacles avoidance and dynamic constraints such as hard bounds and non-holonomic characteristic of AUV are the main motivation of this research. For this purpose, a closed-loop rapidly-exploring random tree (CL-RRT) algorithm is presented. This CL-RRT consists of three tightly coupled components: a RRT algorithm, three fuzzy proportional-derivative controllers for heading and diving control and a six degree-of-freedom nonlinear AUV model. The branches of CL-RRT are expanded in the configuration space by considering the kinodynamic constraints of AUV. The feasibility of each branch and random offspring vertex in the CL-RRT is checked against the mentioned constraints of AUV. Next, if the planned branch is feasible by the AUV, then the control signals and related vertex are recorded through the path planner to design the final path. This proposed algorithm is implemented on a single board computer (SBC) through the xPC Target and then four test-cases are designed in 3D space. The results of the processor-in-the-loop tests are compared by the conventional RRT and indicate that the proposed CL-RRT not only in a rapid manner plans an initial path, but also the planned path is feasible by the AUV. 相似文献
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A technique for autonomous underwater vehicle route planning 总被引：1，自引：0，他引：1
If an underwater vehicle is to be completely autonomous, it must have the ability to plan paths around obstacles in order to operate safely. Many solutions to the problem of planning the path of a robot around obstacles have been proposed, but all are limited in some way. An algorithm using artificial potential fields to aid in path planning is presented. The planning consists of applying potential fields around obstacles and using these fields to select a safe path. The advantage of using potential fields is that they offer a relatively fast and effective way to solve for safe paths. A trial path is chosen and then modified under the influence of the potential field until an appropriate path is found. By considering the entire path, the problem of being trapped in a local minimum is greatly reduced, allowing the method to be used for global planning. The algorithm was tried with success on many different planning problems. The examples provided illustrate the algorithm's application to two- and three-dimensional planning problems 相似文献
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This paper describes the estimation of hydrodynamic coefficients and the control algorithm based on a nonlinear mathematical modeling for a test bed autonomous underwater vehicle (AUV) named by SNUUV I (Seoul National University Underwater Vehicle I).A six degree of freedom mathematical model for SNUUV I is derived with linear and nonlinear hydrodynamic coefficients, which are estimated with the help of a potential code and also the system identification using multi-variable regression.A navigation algorithm is developed using three ranging sonars, pressure sensor and two inclinometers keeping towing tank applications in mind. Based on the mathematical model, a simulation program using a model-based control algorithm is designed for heading control and wall following control of SNUUV I.It is demonstrated numerically that the navigation system together with controller guides the vehicle to follow the desired heading and path with a sufficient accuracy. Therefore the model-based control algorithm can be designed efficiently using the system identification method based on vehicle motion experiments with the appropriate navigation system. 相似文献
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This paper proposes a nonlinear robust adaptive control strategy to force a six degrees of freedom underactuated underwater vehicle with only four actuators to follow a predefined path at a desired speed despite of the presence of environmental disturbances and vehicle’s unknown physical parameters. The proposed controller is designed using Lyapunov’s direct method, the popular backstepping and parameter projection techniques. The closed loop path following errors can be made arbitrarily small. Interestingly, it is shown that our developed control strategy is easily extendible to situations of practical importance such as parking and point-to-point navigation. Numerical simulations are provided to illustrate the effectiveness of the proposed methodology. 相似文献