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Distributed consensus-based formation control for nonholonomic wheeled mobile robots using adaptive neural network

机译:基于自适应神经网络的非完整轮式移动机器人基于共识的分布式编队控制

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摘要

This paper investigates the distributed formation control problem for multiple nonholonomic wheeled mobile robots. A variable transformation is first proposed to convert the formation control problem into a state consensus problem. Then, when the dynamics of the mobile robots are considered, the distributed kinematic controllers and neural network torque controllers are derived for each robot such that a group of nonholonomic mobile robots asymptotically converge to a desired geometric pattern along the specified reference trajectory. The specified reference trajectory is assumed to be the trajectory of a virtual leader whose information is available to only a subset of the followers. Also the followers are assumed to have only local interaction. Moreover, the neural network torque controllers proposed in this work can tackle the dynamics of robots with unmodeled bounded disturbances and unstructured unmodeled dynamics. Some sufficient conditions are derived for accomplish the asymptotically stability of the systems based on algebraic graph theory, matrix theory, and Lyapunov control approach. Finally, simulation examples illustrate the effectiveness of the proposed controllers.
机译:本文研究了多个非完整的轮式移动机器人的分布式编队控制问题。首先提出了变量转换,以将地层控制问题转换为状态共识问题。然后,当考虑移动机器人的动力学时,为每个机器人导出分布式运动学控制器和神经网络扭矩控制器,以使一组非完整的移动机器人沿着指定的参考轨迹渐渐收敛到所需的几何图案。假定指定的参考轨迹是虚拟领导者的轨迹,其信息仅对跟随者的子集可用。此外,假定跟随者仅具有局部互动。此外,这项工作中提出的神经网络转矩控制器可以解决具有未建模的有限扰动和未建模的非建模动力学的机器人的动力学问题。基于代数图论,矩阵论和李雅普诺夫控制方法,得出了一些足以实现系统渐近稳定的条件。最后,仿真示例说明了所提出控制器的有效性。

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