自适应控制柔性关节机器人，实时补偿未知刚度变化。
Adaptive Control of Motor-Position-Controlled Flexible Joint Robots with Uncertain Joint Stiffness
- 基于隐式控制律与依赖控制输入的回归矩阵，在线估计关节非线性刚度。
- 实验验证在非线性刚度下仍能稳定控制，误差显著降低。
- 适合关节刚度随工况或老化变化的高精度机器人系统。
采用位置控制电机的柔性关节机器人模型控制依赖于精确的关节柔度知识。然而实际中，物理弹性元件的特性会随工作条件变化并因磨损老化而缓慢退化，导致精确刚度模型难以获取。为提升此类系统的模型控制性能，本文提出一种自适应控制方法，可实时更新各关节不确定的非线性力矩-变形关系估计。与传统无弹性机器人的自适应控制不同，本方法采用隐式控制律和依赖控制输入的回归矩阵，以应对关节刚度不确定性。分析了电机位置控制器引入误差对鲁棒性的影响，并在具有非线性刚度特性的柔性关节上进行了实验，结果证明该方法的有效性。
原文摘要 · Abstract (English)
Model-based control of flexible joint robots with position-controlled actuators relies on accurate knowledge of the joint compliance. In practice, precise stiffness models are often unavailable as the properties of physical elastic elements vary with operating conditions and slowly change over time due to wear and aging. To improve model-based control of these systems, we propose an adaptive control approach in this work, which updates an estimate of the uncertain, nonlinear torque-deflection relation of each joint. As opposed to classical adaptive control approaches for non-elastic robots, we rely on an implicit control law and a control-input-dependent regressor matrix to account for the uncertain joint stiffness. We analyze robustness of the approach against errors induced by the motor position controller. Experimental results on a flexible joint with nonlinear stiffness characteristics demonstrate the effectiveness of the proposed approach.
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