| 基于神经网络的机器人阻抗控制研究 |
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| 引用本文： | 袁军,黄心汉.基于神经网络的机器人阻抗控制研究[J].系统仿真学报,1993,5(3):14-19. |
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| 作者姓名： | 袁军 黄心汉 |
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| 作者单位： | 华中理工大学自控系
(袁军，黄心汉)，华中理工大学自控系(陈锦江) |
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| 摘 要： | 基于神经网络非线性补偿器原理,本文提出了一种机器人新型顺应控制方案,外力信号通过一个二阶阻抗模型来修正期望输入,神经网络非线性补偿器用于补偿机器人有界干扰和未建模动态,提出了机器人模型学习方案,仿真结果证明了学习过程的有效性以及顺应控制的渐近稳定性。
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| 关 键 词： | 机器人 顺应控制 阻抗控制 神经网络 |
Impedance Control of Robotic Manipulator Based on Neural Network |
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| Yuan Jim Huang Xinhan Chen Jinjang Hua Zhong,University of Technolgy.Impedance Control of Robotic Manipulator Based on Neural Network[J].Journal of System Simulation,1993,5(3):14-19. |
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| Authors: | Yuan Jim Huang Xinhan Chen Jinjang Hua Zhong University of Technolgy |
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| Institution: | Yuan Jim Huang Xinhan Chen Jinjang Hua Zhong
University of Technolgy |
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| Abstract: | Based on the principle of nonlinear compesator of neural network, this paper presents a new type of compliant control for robotic manipulator. The expected input is revised by external signal through two-order impedance model and noulinear compesator of neural network is used to compesate the bounded disturbance and unmodelling dynamics of robotic manipulator. This paper also presents model learning for control of robotic manipulator. The simulation results have illustrated effectiveness of learning procedure and asymptotic stability of compliant control. |
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| Keywords: | Robotic manipulator Impedance Control B-P neural network Learning algorithm |
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