Switched Adaptive Control Methods for Electrical Stimulation Induced Cycling

该项目将创造新的控制方法，以最大限度地提高神经系统疾病（NCs）患者（包括中风、脊髓损伤和创伤性脑损伤）常用康复治疗的有效性。功能性电刺激（FES）循环使用外部施加的一系列电压，使个人的腿部肌肉收缩，以推动平躺循环。重复的、协调的骑车运动可以帮助恢复肢体功能。如果需要，可以使用电动马达来增强人体自身的肌肉。这个项目将决定如何在不同的肌肉群和马达之间切换，以确保所需的行为，尽管个体之间的肌肉力量和耐力存在差异。例如，该项目将检查使FES循环能够在已知时间间隔内适应新参与者的个人属性的方法。研究结果将在NCs患者群体中进行验证，以证明临床疗效。该项目将通过改善非传染性疾病患者的生活质量来促进国民健康。除了这些直接的好处外，该项目还将向优秀的本科生介绍生物力学这一关键领域的先进研究方法。该项目将产生不确定非线性混合系统控制设计的新方法，包括自适应策略和定时条件。该项目的基本方面包括：1)基于Lyapunov定理的公式，以促进具有非严格Lyapunov函数的稳定子系统之间任意切换的自适应控制；2)制定了在非受控（不稳定）子系统和自适应受控子系统之间切换时保证稳定性的驻留时间切换条件，以及从给定的非严格Lyapunov函数中学习严格Lyapunov函数的数据驱动方法；3)可以将系统响应约束在特定状态空间区域内的切换控制器的公式。广义的理论成果将包括对非线性系统和机器人社区的新见解。实验结果将为特定患者群体的纵向临床研究提供突破口，具有改善临床结果的潜力。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project will create new control methods to maximize the effectiveness of a commonly prescribed rehabilitation therapy for individuals with neurological conditions (NCs), including stroke, spinal cord injury, and traumatic brain injury. Functional Electrical Stimulation (FES) cycling uses an externally applied sequence of voltages to cause the individual's leg muscles to contract to propel a recumbent cycle. The repetitive, coordinated motions of cycling can help restore limb function. An electric motor is available to augment the person's own muscles, if needed. This project will determine how to switch between different muscle groups and the motor to ensure desired behaviors, despite differences in muscle strength and endurance between individuals. For example, the project will examine methods to enable an FES cycle to adapt to the individual attributes of a new participant within a known time interval. The results will be validated in populations of individuals with NCs to demonstrate clinical efficacy. This project will advance the national health by improving the quality of life for individuals with NCs. In addition to these direct benefits, the project will introduce top undergraduate students to advanced research methods in this critical area of biomechanics.This project will result in new methods of control design for uncertain nonlinear hybrid systems, including adaptation strategies and timing conditions. Essential aspects of the project include 1) the formulation of Lyapunov-based theorems to facilitate adaptive control for arbitrary switching between stable subsystems with a non-strict Lyapunov function; 2) the formulation of a dwell-time switching condition to ensure stability when switching between an uncontrolled (unstable) and adaptive controlled subsystems, as well as a data-driven method for learning a strict Lyapunov function from a given non-strict Lyapunov function; 3) the formulation of a switching controller that can bound the system response within a particular region of state space. Generalized theoretical outcomes will include new insights for the nonlinear systems and robotics communities. The experimental results will provide an inroad to longitudinal clinical studies in specific patient populations, with the potential to improve clinical outcomes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.