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Sensor and actuator fault detection and isolation using two model based approaches: Application to an autonomous electric vehicle

机译:使用基于模型的两种方法对传感器和执行器进行故障检测和隔离:在自动驾驶汽车中的应用

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In this paper, two model based approaches are proposed in order to detect and to isolate sensor and actuator faults on an electric autonomous vehicle. The first one is based on sliding mode observers. The principle is to reconstruct the state vector and the outputs of the system by sliding mode observers and to compare the estimated outputs with those measured, the obtained difference is considered as residual. The second approach rests on nonlinear analytical redundancy (NLAR) and consists to eliminate the unknown states and variables in order to obtain relations where all variables are known. The objective of this paper is to show the interest of the two approaches for detecting sensor or actuator faults of autonomous electric vehicle. Simulation results show that the method of NLAR is more adequate to detect actuator faults and the sliding mode observer is better for detecting sensor faults.
机译:本文提出了两种基于模型的方法,以检测和隔离电动自动驾驶汽车上的传感器和执行器故障。第一个基于滑模观察器。原理是通过滑模观测器重建状态向量和系统的输出,并将估计的输出与测量的输出进行比较,将获得的差异视为残差。第二种方法基于非线性分析冗余(NLAR),包括消除未知状态和变量,以便获得所有变量均已知的关系。本文的目的是展示两种检测自动电动汽车传感器或执行器故障的方法的兴趣。仿真结果表明,NLAR方法更适合于检测执行器故障,而滑模观测器更适合于检测传感器故障。

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