水下机器人高度信息融合与欠驱动地形跟踪控制

研究了配置高度计和多普勒速度计(DVL)的欠驱动水下机器人地形跟踪控制问题.采用Takagi-Sugeno推理方法对高度计和DVL两种传感器的高度信息进行融合,提高了高度信息感知能力.将地形跟踪分为速度控制和深度控制问题,分别使用S面控制方法设计速度控制器和反步法设计欠驱动深度控制器.最后,通过实际海洋实验对研究的方法进行了验证,实验结果表明该文提出的方法是有效的.     

基于自抗扰的自主水下航行器地形跟踪控制

为保证自主水下航行器在进行地形跟踪任务时,可以更好地抵抗外界环境及自身信号传输的干扰作用,提出一种基于自抗扰控制技术的地形跟踪控制方法,可以将地形跟踪转化为水下机器人的纵倾控制,并设计有运动保护机制。在仿真实验中,利用所设计方法,进行了三维运动仿真,模拟了机器人从水面到水下完成地形跟踪任务的全过程,并与基于PID控制方法的控制器进行比较。结果表明,基于自抗扰控制技术的地形跟踪控制方法能够准确完成预定任务,同时,相比于基于PID的跟踪方法,能够更有效地抑制干扰所造成的超调和震颤等现象,具有更优的控制效果。     

A nonlinear bottom-following controller for underactuated autonomous underwater vehicles

The bottom-following problem for underactuated autonomous underwater vehicles^(AUV) was addressed by a new type of nonlinear decoupling control law. The vertical bottom-following error and pitch angle error are stabilized by means of the stern plane, and the thruster is left to stabilize the longitudinal bottom-following error and forward speed. In order to better meet the need of engineering applications, working characteristics of the actuators were sufficiently considered to design the proposed controller. Different from the traditional method, the methodology used to solve the problem is generated by AUV model without a reference orientation, and it deals explicitly with vehicle dynamics and the geometric characteristics of the desired tracking bottom curve. The estimation of systemic uncertainties and disturbances and the pitch velocity PE (persistent excitation) conditions are not required. The stability analysis is given by Lyapunov theorem. Simulation results of a full nonlinear hydrodynamic AUV model are provided to validate the effectiveness and robustness of the proposed controller.     

基于高度计信息处理的欠驱动无人水下航行器地形跟踪控制

针对高度测量信息不准确情况下的欠驱动无人水下航行器(UUV)地形跟踪控制问题,结合欠驱动UUV的固有特性,提出了一种基于反步法的非线性海底地形跟踪控制方法。首先,针对高度计受海水温度和盐度等海洋环境的干扰而导致高度测量信息不准确的问题,采用卡尔曼滤波器对高度测量信息进行处理,提高高度信息的准确性;然后,基于Lyapunov稳定性理论和反步法设计了非线性地形跟踪控制器,并证明了控制系统的渐近稳定性;最后,分别通过仿真实验和海试实验对所提出的方法进行验证。结果表明,基于高度信息滤波处理的欠驱动UUV非线性地形跟踪控制器能够实现精确的地形跟踪控制。     

Bottom-Following for Remotely Operated Vehicles: Algorithms and Experiments

This paper addresses the problem of designing high precision bottom followers for remotely operated vehicles. In the framework of hierarchical control architectures able to uncouple the robot's kinematics (guidance) and dynamics (velocity control), the task of bottom-following is accomplished by suitable guidance task functions, which enable the system to handle unmodeled, i.e., not measured or estimated, kinematics interactions between the robot and the operating environment. In order to increase the bottom followers' reliability, the paper discusses possible techniques for modeling and handling the environmental and measurement uncertainty in the estimate of the local interactions between the vehicle and the operating environment, i.e., altitude and bottom slope. In particular, according to at-sea operational experience, the problem of managing dropouts due to erroneous tracking of multi-path echoes by the ROV altimeter(s) is addressed. Results of a large set of pool trials carried out with the Romeo ROV are reported and discussed.