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Adaptive Neural Network Consensus Based Control of Robot Formations

机译:基于自适应神经网络共识的机器人编队控制

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In this paper, adaptive consensus based formation control scheme is derived for mobile robots in a pre-defined formation when full dynamics of the robots which include inertia, Corolis, and friction vector are considered. It is shown that dynamic uncertainties of robots can make overall formation unstable when traditional consensus scheme is utilized. In order to estimate the affine nonlinear robot dynamics, a NN based adaptive scheme is utilized. In addition to this adaptive feedback control input, an additional control input is introduced based on the consensus approach to make the robots keep their desired formation. Subsequently, the outer consensus loop is redesigned for reduced communication. Lyapunov theory is used to show the stability of overall system. Simulation results are included at the end.
机译:在本文中,考虑了包括惯性,Corolis和摩擦矢量在内的机器人的全部动力学特性,推导了基于自适应共识的编队控制方案,用于预定义编队。结果表明,采用传统的共识方案时,机器人的动态不确定性会使整体结构不稳定。为了估计仿射非线性机器人动力学,利用了基于神经网络的自适应方案。除了此自适应反馈控制输入外,还基于共识方法引入了其他控制输入,以使机器人保持所需的状态。随后,重新设计外部共识循环以减少通信。李雅普诺夫理论用来证明整个系统的稳定性。最后包括仿真结果。

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