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类Lyapunov理论在类人形机器人任务空间内跟踪的应用 被引量：1

Application of Lyapunov-like methodology for a humanoid robot tracking in task space
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摘要 考虑了类人形机器人的各种不确定因素,提出了其手臂控制的新方法.基于类Lyapunov方法,设计出具有鲁棒性功能的任务空间控制器.该方法得到的控制器不但在有限确定时间内达到稳定跟踪,而且不需要雅可比矩阵求逆,对一定类型的外部干扰具有鲁棒性功能.最后通过数值仿真显示了所得结果的有效性及其应用方法. A new method for the arm control of a humanoid robot is proposed under the consideration of many uncertain factors.Based on Lyapunov-like methodology,controllers in task space were constructed which had a robust effect.Being different from common results,the obtained controllers not only guarantee tracking stability within a finite prescribed time,but also need not solve the inverse of Jacobian matrix and achieve robustness with respect to a class of bounded disturbance.Finally,numerical simulation results were given to illustrate the proposed methods.
作者 刘英卓 王越超 席宁
机构地区 中国科学院沈阳自动化研究所机器人学重点实验室
出处 《控制理论与应用》 EI CAS CSCD 北大核心 2004年第3期351-356,共6页 Control Theory & Applications
基金 国家"十五""863"资助项目(2001AA422170).
关键词 类人形机器人 自适应控制 神经网络 humanoid robot adaptive control neural network
分类号 TP24 [自动化与计算机技术—检测技术与自动化装置]
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参考文献4

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二级参考文献7

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共引文献3

同被引文献28

  • 1彭济根,倪元华,乔红.柔性关节机操手的神经网络控制[J].自动化学报,2007,33(2):175-180. 被引量：23
  • 2丰保民,马广程,温奇咏,王常虹.任务空间内空间机器人鲁棒智能控制器设计[J].宇航学报,2007,28(4):914-919. 被引量：25
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  • 7Wang C, Hill D J. Learning from neural control. IEEE Transactions on Neural Networks, 2006, 17(1): 130-146.
  • 8Wang C, Hill D J. Deterministic Learning Theory for Identi- fication, Recognition and Control Boca Raton: CRC Press, 2009.
  • 9Liu T F, Wang C, Hill D J. Learning from neural control of nonlinear systems in normal form. Systems & Control Letters, 2009, 58(9): 633-638.
  • 10Wang C, Wang M, Liu T F, Hill D J. Learning from ISS- modular adaptive NN control of nonlinear strict-feedback systems. IEEE Transactions on Neural Networks and Learn- ing Systems, 2012, 23(10): 1539-1550.

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控制理论与应用
2004年 第3期

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