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- 저자 : Rongxin Cui (검색결과 2 건)
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Moving long baseline positioning algorithm with uncertain sound speed
Weisheng Yan,Wei Chen,Rongxin Cui 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.9
This paper presents a Moving long baseline (MLBL) positioning algorithm for the underwater target considering the uncertainunderwater sound speed. First, the positioning and the sound speed models are established. To tackle the uncertain sound speed, auncertain Least squares (ULS) positioning algorithm is applied to estimate the target position and the sound speed. Then it is essentiallyshown that four mobile buoys are necessarily (at least) required to locate the target. Further, it is found that under a singularityscenario in which the ranges between the target and each of the mobile buoys are equal, there is no solution to the positioning accordingto the classical geometrical equations. In order to solve this singularity problem, an ULS-based unscented Kalman filter(UKF) algorithm is proposed to obtain the estimated solution. Simulation results illustrate the effectiveness of proposed methods.
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A Coverage Algorithm for Multiple Autonomous Surface Vehicles in Flowing Environments
Weisheng Yan,Lei Zuo,Rongxin Cui,Jian Gao 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.2
This paper is concerned with the coverage problem with multiple autonomous surface vehicles (ASVs) intime-varying flowing environment, where the interest information distribution is unknown to the coverage networks. While taking the model parameter uncertainty into consideration, a decentralized, adaptive control law is proposedsuch that the coverage network will converge to the optimal assigned region from arbitrary positions. For easeof exploration, we first investigate the static coverage problem of two-agent systems in flowing environment andpresent an example by extending the two-agent systems into the general case. In addition, Gaussian Estimationis introduced to predict the value of the sensory function through the sampled measurements. By using the staticcoverage partition as theoretical foundation, we transform the optimal coverage control into the moving targettracking problems, where the target is the centroid of the assigned region for each ASV. Based on these techniques,a decentralized kinematic control algorithm is developed to navigate the multi-ASV systems. Furthermore, theadaptive back-stepping techniques are employed to extend the kinematic controller into dynamic case with uncertainmodel parameters. Finally, simulation studies are provided to demonstrate the feasibility and effectiveness of theproposed approaches.
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