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NEURAL NETWORK-BASED FAULT-TOLERANT CONTROL METHOD OF UNDERACTUATED AUTONOMOUS VEHICLE

机译:基于神经网络的动力不足汽车故障容错控制方法

摘要

The present invention relates to a neural network-based fault-tolerant control method of autonomous vehicle underactuated. The present invention includes reconstruction of kinematic model and cooperative model based on a state transition with an underactuated device to tolerate a free unmanned moving body that lacks control input relative to a degree of freedom and follow a target behavior, compensation for lack of a control input, fault-tolerant input control input estimation using Nussbaum technique, and precise following and fault-tolerant control and underactuated operation on the target, by setting the bound condition of a following error.
机译:本发明涉及一种基于神经网络的欠驱动自动驾驶汽车的容错控制方法。本发明包括基于状态转换的运动模型和协作模型的重构,该状态转换具有欠驱动装置以容忍相对于自由度缺乏控制输入并遵循目标行为的自由无人移动体,补偿缺乏控制输入,使用Nussbaum技术进行容错输入控制输入估计,以及通过设置跟随误差的约束条件,对目标进行精确的跟随和容错控制以及欠驱动操作。

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