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| 标 题： |
A UNIFIED APPROACH TO DESIGN OF ADAPTIVE AND REPETITIVE CONTROLLERS FOR ROBOTIC MANIPULATORS
机器人机械臂自适应与重复控制律设计的统一方法 |
| 作 者： |
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| 关键词： |
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| 出版年： |
1988 |
| 文集名： |
CROSSING BRIDGES: ADVANCES IN FLEXIBLE AUTOMATION AND ROBOTICS, vol.1
跨越桥梁：柔性自动化与机器人技术进展，第1卷 |
| 会议名： |
THE USA-JAPAN SYMPOSIUM ON FLEXIBLE AUTOMATION
美日柔性自动化研讨会 |
| 届 次： |
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| 摘 要： |
A unified approach, based on Lyapunov theory, for synthesis and stability analysis of adaptive and repetitive controllers for mechanical manipulators is presented. This approach utilizes the passivity properties of manipulator dynamics to derive control laws which guarantee asymptotic trajectory following, without requiring exact knowledge of the manipulator dynamic parameters. The manipulator overall controller consists of a fixed PD action and an adaptive and/or repetitive action, adjusted based on a linear combination of the tracking velocity and position errors, for feed-forward compensations. The repetitive compensator is recommended for tasks in which the desired trajectory is periodic. The repetitive control input is adjusted periodically without requiring knowledge of the explicit structure of the manipulator model. The adaptive compensator, on the other hand, may be used for more general trajectories, however, explicit information regarding the dynamic model structure is required in parameter adaptation, which takes place continuously. A hybrid version of the repetitive controller, which is needed for discrete time implementations, is derived and its global stability proven. A simulation study is conducted to evaluate the performance of the repetitive controller, and its hybrid version, applied to Berkeley/NSK SCARA type robot arm.
本文提出了一种基于Lyapunov理论的统一方法，用于机械手自适应与重复控制器的合成及稳定性分析。该方法利用机械手动力学的消逝性特性，推导出能够保证轨迹渐近跟踪的控制律，且无需精确掌握机械手动力学参数。整个机械手控制器由一个固定的PD动作和一个自适应或重复动作组成，重复动作根据跟踪速度与位置误差的线性组合进行调整，以实现前馈补偿。对于期望轨迹为周期性的任务，建议采用重复补偿器。重复控制输入可周期性调整，而无需了解机械手模型的显式结构。另一方面，自适应补偿器可用于更一般的轨迹，但其参数自适应过程需要持续获取动力学模型结构的明确信息。推导出一种适用于离散时间实现的重复控制器混合版本，并证明其全局稳定性。通过仿真研究评估了该重复控制器及其混合版本在伯克利/NSK SCARA型机械臂上的性能表现。 |
| 中文内容为网络AI翻译，专业术语未必准确，仅供参考。 |
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