Adaptive Neural Network Control of Robotic Manipulators

S. Ge, Tong-heng Lee, C. Harris
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引用次数: 537

Abstract

There has been considerable research interest in neural network control of robots, and satisfactory results have been obtained in solving some of the special issues associated with the problems of robot control in an "on-and-off" fasion. This text is dedicated to issues on adaptive control of robots based on neural networks. The text has been tailored to give a comprehensive study of robot dynamics, present structured network models for robots, and provide systematic approaches for neural network based adaptive controller design for rigid robots, flexible joint robots, and robots in constraint motion. Rigorous proof of the stability properties of adaptive neural network controllers is provided. Simulation examples are also presented to verify the effectiveness of the controllers, and practical implementation issues associated with the controllers are also discussed.
机械臂的自适应神经网络控制
机器人的神经网络控制已经引起了相当大的研究兴趣,并在解决机器人“开-关”控制问题中的一些特殊问题方面取得了令人满意的结果。本文主要研究基于神经网络的机器人自适应控制问题。本文已量身定制,以提供机器人动力学的全面研究,目前结构化的网络模型的机器人,并提供系统的方法,基于神经网络的自适应控制器设计的刚性机器人,柔性关节机器人,机器人在约束运动。给出了自适应神经网络控制器稳定性的严格证明。仿真实例验证了控制器的有效性,并对控制器的实际实现问题进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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