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首页> 外文会议>Mediterranean Conference on Medical and Biological Engineering and Computing >Feedback-Error Learning Control for Powered Assistive Devices
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Feedback-Error Learning Control for Powered Assistive Devices

机译：供电辅助设备的反馈错误学习控制

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Active orthoses (AOs) are becoming relevant for user-oriented training in gait rehabilitation. This implies efficient responses of AO's low-level controllers with short time modeling for medical applications. This thesis investigates, in an innovative way, the performance of Feedback-Error Learning (FEL) control to time-effectively adapt the AOs' responses to user-onented trajectories and changes in the dynamics due to the interaction with the user. FEL control comprises a feedback PID controller and a neural network feedforward controller to promptly learn the inverse dynamics of two AOs. It was carried out experiments with able-bodied subjects walking on a treadmill and considering external disturbances to user-AO interaction. Results showed that the FEL control effectively tracked the user-oriented trajectory with position errors between 5% to 7%, and with a mean delay lower than 25 ms. Compared to a single PID control, the FEL control decreased by 16.5% and 90.7% the position error and delay, respectively. Moreover, the feedforward controller was able to learn the inverse dynamics of the two AOs and adapt to variations in the user-oriented trajectories, such as speed and angular range, while the feedback controller compensated for random disturbances. FEL demonstrated to be an efficient low-level controller for controlling AOs during gait rehabilitation.
机译：活跃的结果（AOS）正越来越重要，与您在步态康复的面向用户的培训相关。这意味着AO的低级控制器对医疗应用短时间模型的低级控制器的有效响应。本文以一种创新的方式调查反馈误区（FEL）控制的性能，以时间有效地使AOS对用户的响应对用户的响应以及由于与用户的交互而改变动态。 FEL控制包括反馈PID控制器和神经网络前馈控制器，以迅速学习两个AO的逆动态。它是通过在跑步机上行走并考虑到User-AO互动的外部干扰的实验。结果表明，FEL控制有效地跟踪了面向用户导向的轨迹，其位置误差在5％至7％之间，并且平均延迟低于25毫秒。与单个PID控制相比，FEL控制分别下降了16.5％和90.7％的位置误差和延迟。此外，前馈控制器能够学习两个AO的逆动力学，并适应用户取向轨迹的变化，例如速度和角度范围，而反馈控制器补偿了随机干扰。 FEL被证明是一种用于在步态康复期间控制AO的有效的低级控制器。

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