Real-Time Finite Element Methods for Controlling Flexible Biomechatronic Systems

控制灵活生物机电系统的实时有限元方法

• 批准号: RGPIN-2021-03073
• 负责人: Faieghi, Mohammadreza
• 金额: $ 1.97万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742364
• 关键词: Real; Time; Finite; Element; Methods

The rise of biomechatronics has enabled the development of novel interventions not only in the areas of healthcare and rehabilitation but also in the areas of human factors and ergonomics. Examples range from surgical robotics to exoskeletons that are used to improve healthcare outcomes as well as from active-controlled garments to morphing seats capable to adapt to one's posture to minimize discomfort. Such systems are generally studied within the realm of multibody systems. When elastic deformations of structural members are considered, these systems are often modeled as flexible multibody systems, for example, to control a soft surgical robot or to reduce stress on the human musculoskeletal system during interactions with a robotic device. However, elasticity complicates the design of the control system, making most existing control methods obsolete when dealing with nonlinear geometrical and material effects. The finite element method (FEM) is the standard approach in studying complex systems; however, its use in real-time control is rather rare due to its large computational load. Consequently, there is a paucity of theoretical approaches able to use finite element analysis for the control of systems. The goal of this research program is to address this gap of knowledge in order to extend FEM towards real-time control systems, especially for controlling flexible biomechatronic systems. To fulfill the above objective, the proposed research program consists of three pillars, including (1) instrumentation and calibration (2) real-time FEM solver, and (3) control law. The first pillar will develop optimization-based methods for model calibration, and computer vision-based sensing mechanisms to measure system states in real-time FEM-based settings. The second pillar will focus on computationally efficient algorithms for fast solving of finite element problems, by using quasi-Newton methods and parallelization on graphical processing units (GPUs). The third pillar will explore the design of control laws for finite element models using online constrained optimization and Lyapunov methods, followed by sensitivity analysis of the control system with respect to design parameters and modeling and measurement errors. The proposed research program is anticipated to address present challenges associated with the control of flexible biomechatronic systems and will lead to the design of novel wearable devices and soft robotic systems, especially in medicine and ergonomics. This will support several Canadian industry sectors, including healthcare, aerospace, automotive, and manufacturing.

生物机电一体化的兴起不仅在医疗保健和康复领域，而且在人为因素和人体工程学领域都能够开发新的干预措施。例子包括从手术机器人到用于改善医疗保健结果的外骨骼，以及从主动控制服装到能够适应人的姿势以最大限度地减少不适的变形座椅。这样的系统通常在多体系统的领域内进行研究。当考虑结构构件的弹性变形时，这些系统通常被建模为柔性多体系统，例如，以控制软手术机器人或在与机器人设备交互期间减少对人类肌肉骨骼系统的应力。然而，弹性使控制系统的设计复杂化，使得大多数现有的控制方法在处理非线性几何和材料效应时过时。有限元法（FEM）是研究复杂系统的标准方法;然而，由于其计算量大，其在实时控制中的使用相当罕见。因此，有一个缺乏的理论方法，能够使用有限元分析系统的控制。这项研究计划的目标是解决这一知识差距，以扩展有限元对实时控制系统，特别是控制灵活的生物机电系统。 为了实现上述目标，拟议的研究计划包括三个支柱，包括（1）仪器和校准（2）实时有限元求解器，和（3）控制律。第一个支柱将开发基于优化的模型校准方法，以及基于计算机视觉的传感机制，以在基于FEM的实时设置中测量系统状态。第二个支柱将侧重于计算效率高的算法，通过使用拟牛顿法和图形处理单元（GPU）上的并行化快速解决有限元问题。第三个支柱将探讨使用在线约束优化和李亚普诺夫方法设计有限元模型的控制律，然后对控制系统的设计参数和建模及测量误差进行灵敏度分析。拟议的研究计划预计将解决目前与柔性生物机电系统控制相关的挑战，并将导致新型可穿戴设备和软机器人系统的设计，特别是在医学和人体工程学方面。这将支持加拿大的几个行业，包括医疗保健，航空航天，汽车和制造业。