| 改进的BPnn在移动机器人轨迹跟踪中的应用 |
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| 引用本文： | 陈卫东,张燕,朱奇光.改进的BPnn在移动机器人轨迹跟踪中的应用[J].计算机工程与应用,2011,47(8):239-242. |
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| 作者姓名： | 陈卫东 张燕 朱奇光 |
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| 作者单位： | 燕山大学 信息科学与工程学院，河北 秦皇岛 066004 |
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| 基金项目： | 河北省教育厅自然科学研究计划项目 |
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| 摘 要： | 针对BPnn（BP神经网络）在复杂多输入情况下，样本训练速度慢，不能满足实时性要求的缺点，提出了一种把神经网络分割成若干子网分别进行训练来获取更高计算效率的方法。将改进的BPnn应用于移动机器人在未知参数和不确定干扰下的轨迹跟踪控制问题中，提出了一种运动控制器和动力学控制器相结合的改进的计算力矩控制方法，用后退算法设计运动学控制器，用改进的BPnn优化动力学控制器。通过MATLAB数值仿真证明了算法的有效性和正确性。
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| 关 键 词： | 移动机器人 轨迹跟踪 后退算法 改进的反向传播（BP）神经网络 |
| 修稿时间： | |
Application of improved BPnn in trajectory tracking of mobile robot |
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| CHEN Weidong,ZHANG Yan,ZHU Qiguang.Application of improved BPnn in trajectory tracking of mobile robot[J].Computer Engineering and Applications,2011,47(8):239-242. |
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| Authors: | CHEN Weidong ZHANG Yan ZHU Qiguang |
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| Affiliation: | Department of Information Science and Engineering，Yanshan University，Qinhuangdao，Hebei 066004，China |
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| Abstract: | Aiming at the speed of BPnn（BP neural network） is slow and it cannot meet the real-time request in complex multiple input conditions,a method of partitioning BPnn into several smaller subnets in order to obtain more efficient computation is proposed.Using the improved BPnn to the trajectory tracking problem of mobile robot with unknown parameters and interferences,an improved computed-torque control by the integration of a kinematic controller and a dynamic controller is proposed.The kinematic controller is designed by the backstepping technology and the dynamic controller is optimized by the improved BPnn.MATLAB numerical simulations are provided to show the effectiveness and correctness of the suggested approach. |
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| Keywords: | mobile robot trajectory tracking backstepping algorithm improved Back Propagation neural network（BPnn） |
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