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Collision avoidance for a mobile robot based on radial basis function hybrid force control technique 下载免费PDF全文
Collision avoidance is always difficult in the planning path for a
mobile robot. In this paper, the virtual force field between a
mobile robot and an obstacle is formed and regulated to maintain a
desired distance by hybrid force control algorithm. Since
uncertainties from robot dynamics and obstacle degrade the
performance of a collision avoidance task, intelligent control is
used to compensate for the uncertainties. A radial basis function
(RBF) neural network is used to regulate the force field of an accurate
distance between a robot and an obstacle in this paper and then
simulation studies are conducted to confirm that the proposed
algorithm is effective. 相似文献
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提出了一种带有预测函数的Hénon 混沌系统的广义预测控制快速算法.首先用时变遗忘因子的递推最小二乘方法辨识混沌系统,然后在广义预测控制的基础上引入了预测函数控制方法,并充分利用了预测信息的补偿作用.这种算法克服了广义预测控制中求解逆矩阵的缺点,提高了系统响应的速度,并且具有较强的跟踪给定信号、抑制系统参数摄动和随机噪声的能力.仿真结果验证了该方法的有效性.
关键词:
广义预测控制
预测函数
Hénon 混沌系统
参数辨识 相似文献
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