Soft actuators offer compliant and safe interaction with an unstructured environment compared to their rigid counterparts. However, control of these systems is often challenging because they are inherently under-actuated, have infinite degrees of freedom (DoF), and their mechanical properties can change by unknown external loads. Existing works mainly relied on discretization and reduction, suffering from either low accuracy or high computational cost for real-time control purposes. Recently, we presented an infinite-dimensional feedback controller for soft manipulators modeled by partial differential equations (PDEs) based on the Cosserat rod theory. In this study, we examine how to implement this controller in real-time using only a limited number of actuators. To do so, we formulate a convex quadratic programming problem that tunes the feedback gains of the controller in real time such that it becomes realizable by the actuators. We evaluated the controller's performance through experiments on a physical soft robot capable of planar motions and show that the actual controller implemented by the finite-dimensional actuators still preserves the stabilizing property of the desired infinite-dimensional controller. This research fills the gap between the infinite-dimensional control design and finite-dimensional actuation in practice and suggests a promising direction for exploring PDE-based control design for soft robots.
翻译:柔性执行器相比其刚性对应物拥有具有顺应性和安全性的与非结构化环境交互能力。但是,由于柔性机器人在机械设计上的固有特性,具有无限自由度,受外部载荷影响机械特性变化大,因此对其进行控制是一项具有挑战性的任务。现有研究主要依靠离散化和降维等策略进行控制,这种方法不仅精度低,而且实时性差,计算成本高。最近,我们基于Cosserat rod理论提出了一种基于偏微分方程(PDE)模型的柔性机械的无限维反馈控制器。本研究探讨如何只使用有限数量的执行器实时实现这种控制器。为此,我们提出了一个凸二次规划问题,通过实时调节反馈增益,使控制器能够通过执行器实现。我们通过对能够进行平面运动的物理软机器人的实验来评估控制器性能,并且表明实际使用有限维执行器实现的控制器仍然保持所需的无限维稳定特性。本研究填补了无限维控制设计与实际的有限维执行的差距,并为探索基于PDE的柔性机器人控制设计提供了一个有前途的方向。