Abstract: For telerobotic system, an online PoT (performance of teleoperator) identification method and a PoT based control framework for the mobile telerobotic system are proposed. Firstly, 5 PoT indicators are extracted by analyzing electroencephalography (EEG) signals of the teleoperator, and BP (backpropagation) neural network is used to model those indicators, so that the PoT can be identified online. Then, a dynamic adjustment strategy of control weights in a teleoperation shared control system is proposed based on PoT. Finally, experiments on the online PoT identification and the PoT based shared control teleoperation are performed with 3 teleoperators. The results demonstrate the effectiveness of the proposed method in PoT online identification, as well as the enhancement of teleoperation efficiency and safety by the PoT based control framework.