Simultaneous Motion and Stiffness Control for Soft Pneumatic Manipulators based on a Lagrangian-based Dynamic Model
Simultaneous Motion and Stiffness Control for Soft Pneumatic Manipulators based on a Lagrangian-based Dynamic Model
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DOI：
10.23919/acc55779.2023.10156049
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
Yu Mei;Preston Fairchild;Vaibhav Srivastava;C. Cao;Xiaobo Tan
中科院分区：
文献类型：
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作者：
Yu Mei;Preston Fairchild;Vaibhav Srivastava;C. Cao;Xiaobo Tan
具有可调刚度的软连续机械手不仅可以利用高顺应性在未知环境中安全适应，而且可以克服不稳定和低负载能力的缺点。软机械臂的高度非线性以及驱动和刚度调节之间的强耦合使得它们的同步控制具有挑战性。在这项工作中，提出了一种针对软气动机械手同时控制驱动和刚度调节的新方法。在分段恒定曲率假设的情况下，采用具有现实近似的基于拉格朗日的动态模型进行控制设计，其中结合了刚度可调机构的动力学。提出了扩展卡尔曼滤波器（EKF）来估计不可测量的状态，包括刚度和速度。首先在配置空间中开发非线性模型预测控制（NMPC）框架，然后扩展到任务空间，用于在充气和真空压力约束下同时进行运动和刚度控制。仿真结果证明了所提出方法的有效性。
A soft continuum manipulator with tunable stiffness can not only take advantage of high compliance for safe adaptation in unknown environments, but also circumvent the drawbacks of instability and low loading capability. The high nonlinearity of soft manipulators and the strong coupling between actuation and stiffness-tuning make their simultaneous control challenging. In this work, a novel approach to simultaneous control of actuation and stiffness-tuning is proposed for soft pneumatic manipulators. With a piecewise-constant curvature assumption, a Lagrangian-based dynamic model with realistic approximation is used for control design, where the dynamics of the stiffness-tunable mechanism is incorporated. An extended Kalman filter (EKF) is proposed to estimate unmeasurable states including the stiffness and the velocity. A nonlinear model predictive control (NMPC) framework is developed first in the configuration space, and then extended to the task space, for simultaneous motion and stiffness control under inflation and vacuum pressure constraints. Simulation results are presented to support the efficacy of the proposed approach.