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出 处:《船舶》2016年第1期92-99,共8页Ship & Boat
摘 要:无人艇协同编队控制具有重要的军事和商船应用前景。利用多智能体聚集模型,基于leader-follower的目标跟踪,实现了含有模型不确定性与未知海浪流干扰项的多无人艇协同编队控制。采用单隐层神经网络逼近船舶整体未知项和环境干扰,引入一阶滤波器代替反步计算中的微分项,显著减少了计算量。利用时-空解耦方法,各船舶通过交互航迹参数信息,间接实现分散协同编队控制。利用Lyapunov稳定性分析方法,证明闭环系统所有状态和信号收敛于一有界集。通过选择合适参数,可使控制精度误差范围为任意小,仿真结果验证了控制算法的有效性。Cooperation formation control is very important for the unmanned surface vessels(USVs) in military and civil applications. The cooperation formation control for multiple USVs with model uncertainty and the unknown wave-current interference is achieved through the multi-agent aggregation model based on the target tracking by the leader-follower. Moreover, the unknown items and the environmental interference for the whole ship is approached through single hidden layer neural network, and the first-order filter is introduced to replace the differential items in the backstepping calculation, significantly decreasing the amount of calculation. By the timespace decoupling method, the decentralized cooperation formation control will be indirectly reached through the interactive track information for each ship. It is proved that the situation and signals of the closed-loop system are converged to a bounded set by using Lyapunov stability analysis method. The error of the control accuracy becomes arbitrarily small by selecting proper parameters. The control algorithm is then validated by the simulation results.
关 键 词:无人艇 神经网络 不确定性 多智能体 一阶滤波器 编队控制
分 类 号:U664.82[交通运输工程—船舶及航道工程]
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