共查询到20条相似文献,搜索用时 82 毫秒
1.
自治水下机器人机械手系统协调运动研究 总被引:1,自引:0,他引:1
简单描述了自治水下机器人搭载的三功能水下电动机械手的设计,鉴于自治水下机器人-机械手系统运动学冗余、内部可能干涉以及载体圆筒式外形等特点,将惩罚调节因子引入系统运动学伪逆矩阵,保证了关节在允许范围内运动,避免载体大幅度姿态变化及载体与机械手之间的干涉,同时采用梯度投影法优化海流作用下的系统推力。仿真表明,该算法在解决系统冗余度的同时,有效地协调多任务下的系统动作。 相似文献
2.
3.
4.
5.
介绍多水下机器人(UUV)数字仿真平台的硬件结构以及单体UUV和多UUV系统的水动力计算流程,在此基础上利用Windows多线程技术实现多UUV的水动力计算,该方法已经用于多UUV数字仿真平台虚拟环境节点的设计中.系统仿真实验表明该方法设计的应用程序具有良好的执行效率和实时响应能力,为以后多UUV半物理仿真平台的水动力计算和实体多UUV系统水动力系数的验证奠定了基础. 相似文献
6.
7.
水下机器人作业机械手的研究与发展 总被引:6,自引:1,他引:6
水下作业机械手是水下机器人核心组成部分,研究第二、第三代水下机械手技术是水下机器人的重要课题,本文仅就水下作业机械手当前的发展状态,设计原则及智能化技术的研究,提出有关看法,仅供研究水下机械手课题展开讨论。 相似文献
8.
9.
10.
11.
12.
13.
The stability of the motion control system is one of the decisive factors of the control quality for Autonomous Underwater Vehicle (AUV).The divergence of control,which the unstable system may be brought about,is fatal to the operation of AUV.The stability analysis of the PD and S-surface speed controllers based on the Lyapunov' s direct method is proposed in this paper.After decoupling the six degree-of-freedom (DOF) motions of the AUV,the axial dynamic behavior is discussed and the condition is deduced,in which the parameters selection within stability domain can guarantee the system asymptotically stable.The experimental results in a tank and on the sea have successfully verified the algorithm reliability,which can be served as a good reference for analyzing other AUV nonlinear control systems. 相似文献
14.
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。 相似文献
15.
针对水下机器人操纵性优化设计中水动力系数预报问题,在水下机器人水动力预报中引入艇体肥瘦指数概念,确定了水下机器人艇体几何描述的五参数模型。提出采用小波神经网络方法预报水下机器人水动力,确定了神经网络的结构,利用均匀试验设计方法,设计了神经网络的学习样本。研究结果表明,只要确定适当的输入参数,选择适当的学习样本和网络结构,利用小波神经网络方法对水下机器人水动力进行预报可以达到较好的精度。 相似文献
16.
A parallel neural network-based controller (PNNC) is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and it is different from normal adaptive neural network controller in structure. Owing to the introduction of the self-learning part, on-line learning can be performed without sample data in several sample periods, resulting in high learning speed of the controller and good control performance. The desired-state programmer is utilized to obtain better learning samples of the neural network to keep the stability of the controller. The developed controller is applied to the 4-degree of freedom control of the AUV “IUV- IV” and is successful on the simulation platform. The control performance is also compared with that of neural network controller with different structures such as normal adaptive neural network and different learning methods. Current effects and surge velocity control are also included to demonstrate the controller' s performance. It is shown that the PNNC has a great possibility to solve the problems in the control system design of underwater vehicles. 相似文献
17.
A robust neural network controller (NNC) is presented for tracking control of underwater vehicles with uncertainties. The controller is obtained by using backstepping technique and Lyapunov function design in combination with neural network identification. Modeling errors and environmental disturbances are considered in the mathematical model. A two-layer neural network is introduced to compensate the modeling errors, while H∞ control strategy is used to achieve the L2-gain performance. The uniformly ultimately bounded (UUB) stabilities of tracking errors and NN weights are guaranteed through the proposed controller. An on-line NN weights tuning algorithm is also proposed. Good performances of the tracking control system are illustrated by the results of numerical simulations. 相似文献
18.
19.