The prediction of sensor data can help the exoskeleton control system to get the human motion intention and target position in advance, so as to reduce the human-machine interaction force. In this paper, an improved method for the prediction algorithm of exoskeleton sensor data is proposed. Through an algorithm simulation test and two-link simulation experiment, the algorithm improves the prediction accuracy by 14.23 ± 0.5%, and the sensor data is smooth. Input the predicted signal into the two-link model, and use the calculated torque method to verify the prediction accuracy data and smoothness. The simulation results showed that the algorithm can predict the joint angle of the human body and can be used for the follow-up control of the swinging legs of the exoskeleton.

中文翻译：

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基于预测算法参数优化的外骨骼跟踪控制

传感器数据的预测可以帮助外骨骼控制系统提前获取人体运动意图和目标位置，从而减少人机交互作用力。提出了一种改进的外骨骼传感器数据预测算法。通过算法仿真测试和二次链接仿真实验，该算法将预测精度提高了14.23±0.5％，传感器数据平滑。将预测信号输入到双链模型中，并使用计算出的扭矩法验证预测精度数据和平滑度。仿真结果表明，该算法可以预测人体的关节角度，可用于外骨骼摆动腿的跟踪控制。