Model Identification and Control Design for a Humanoid Robot

Model Identification and Control Design for a Humanoid Robot
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仿人机器人模型识别与控制设计

DOI:
10.1109/tsmc.2016.2557227
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发表时间:
2017
影响因子:
8.7
通讯作者:
Sun Changyin
Sun Changyin
中科院分区:
计算机科学1区
文献类型:
--
作者:
He Wei;Ge Weiliang;Li Yunchuan;Liu Yan-Jun;Yang Chenguang;Sun Changyin

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本文对仿人机器人的Devanit-Hartenberg模型进行了模型辨识和自适应控制设计。我们重点研究了机器人上肢6个自由度的建模,使用递归牛顿-欧拉(RNE)公式作为每个关节的坐标系。为了获得足够的激励建模的机器人,粒子群优化方法已被用来优化每个关节的轨迹,这样可以得到满意的参数估计。此外,估计的惯性参数作为初始值的RNE为基础的自适应控制设计,以实现更好的跟踪性能。仿真研究验证了辨识算法的结果,并说明了控制设计的有效性。
In this paper, model identification and adaptive control design are performed on Devanit-Hartenberg model of a humanoid robot. We focus on the modeling of the 6 degree-of-freedom upper limb of the robot using recursive Newton-Euler (RNE) formula for the coordinate frame of each joint. To obtain sufficient excitation for modeling of the robot, the particle swarm optimization method has been employed to optimize the trajectory of each joint, such that satisfied parameter estimation can be obtained. In addition, the estimated inertia parameters are taken as the initial values for the RNE-based adaptive control design to achieve improved tracking performance. Simulation studies have been carried out to verify the result of the identification algorithm and to illustrate the effectiveness of the control design.
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