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A CONTROL STRATEGY FOR DEVELOPED LOWER LIMBS ROBOTIC REHABILITATION CHAIR

机译:开发下肢机器人康复椅的控制策略

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Different lower limbs robotic rehabilitation devices are under study to assist therapists in their work. They are particularly useful to recover gestures altered, affected or lost after traffic accident injury, illness or disability. In this paper, we present our contribution to the robotic therapy improvement. We present a developed robotic rehabilitation device dedicated to the lower limbs rehabilitation. Using functional orthotics it will be applied for functional rehabilitation, allowing the reproduction of the physiological joint trajectories and resume segmental loads of bodily movement, especially walking. We have developed a control strategy for this prototype. The aim was to reproduce all types of exercises usually performed through a therapist. We used a decoupled structure where each joint has its own controller. We proposed a new control law using the kinematic model based on a classic proportional-integral-derivative (PID) controller. Although the device implementations have given good results, the outputs contain a lot of fluctuation, which is detrimental to our equipment. For this purpose, we used a feed-forward neural network (FFNN) controller copied onto the first and adding the error derivative as a second input. The drawbacks noted with the PID controller were eliminated with the FFNN controller.
机译:不同的下肢机器人康复设备正在研究中,以帮助治疗师在工作中。它们特别适用于在交通事故损伤,疾病或残疾后恢复改变,受影响或丢失的姿态。在本文中,我们向机器人治疗改善呈现了我们的贡献。我们提出了一种专用于下肢康复的机器人康复装置。使用功能性矫形器,它将应用于功能康复,允许生理关节轨迹的再现,并恢复身体运动的细分载荷,尤其是行走。我们开发了这种原型的控制策略。目的是再现通常通过治疗师进行的所有类型的练习。我们使用了一个解耦结构,其中每个关节都有自己的控制器。我们提出了一种基于经典比例 - 积分衍生物(PID)控制器的运动模型的新的控制法。虽然设备实现具有良好的结果,但输出包含大量波动,这对我们的设备有害。为此目的,我们使用前馈神经网络(FFNN)控制器复制到第一并将误差导数添加为第二输入。使用FFNN控制器消除了PID控制器的缺点。

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