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http://dx.doi.org/10.3795/KSME-A.2017.41.10.931

Kinematic Model based Predictive Fault Diagnosis Algorithm of Autonomous Vehicles Using Sliding Mode Observer  

Oh, Kwang Seok (Dept. of Mechanical Engineering, Hankyong Nat'l Univ.)
Yi, Kyong Su (School of Mechanical and Aerospace Engineering, Seoul Nat'l Univ.)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.41, no.10, 2017 , pp. 931-940 More about this Journal
Abstract
This paper describes a predictive fault diagnosis algorithm for autonomous vehicles based on a kinematic model that uses a sliding mode observer. To ensure the safety of autonomous vehicles, reliable information about the environment and vehicle dynamic states is required. A predictive algorithm that can interactively diagnose longitudinal environment and vehicle acceleration information is proposed in this paper to evaluate the reliability of sensors. To design the diagnosis algorithm, a longitudinal kinematic model is used based on a sliding mode observer. The reliability of the fault diagnosis algorithm can be ensured because the sliding mode observer utilized can reconstruct the relative acceleration despite faulty signals in the longitudinal environment information. Actual data based performance evaluations are conducted with various fault conditions for a reasonable performance evaluation of the predictive fault diagnosis algorithm presented in this paper. The evaluation results show that the proposed diagnosis algorithm can reasonably diagnose the faults in the longitudinal environment and acceleration information for all fault conditions.
Keywords
Kinematic Model; Fault Diagnosis; Sliding Mode Observer; Autonomous Vehicle; Longitudinal Safety;
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1 Loureiro, R., Benmoussa, S., Touati, Y., Merzouki, R. and Bouamama, B., 2014, "Integration of Fault Diagnosis and Fault-tolerant Control for Health Monitoring of a Class of MIMO Intelligent Autonomous Vehicles," IEEE Transactions on Vehicular Technology, Vol. 63, No. 1, pp. 30-39.   DOI
2 Jeong, Y., Kim, K., Yoon, J., Chong, H., Ko, B. and Yi, K., 2015, "Vehicle Sensor and Actuator Fault Detection Algrithm for Automated Vehicles," In Intelligent Vehicles Symposium(IV), IEEE, pp. 927-932.
3 Tan, C. and Edwards, C., 2002, "Sliding Mode Observer for Detection and Reconstruction of Sensor Faults," Automatica, Vol. 38, pp. 1815-1821.   DOI
4 Yin, S. and Huang, Z., 2015, "Performance Monitoring for Vehicle Suspension System via Fuzzy Positivistic C-means Clustering Based on Accelerometer Measurements," IEEE/ASME Transactions on Mechatronics, Vol. 20, No. 5, pp. 2613-2620.   DOI
5 Kim, Y., Jeon, N. and Lee, H., 2016, "Model Based Fault Detection and Isolation for Driving Motors of a Ground Vehicle," Sensors & Transducers, Vol. 199, No. 4, pp. 67-72.
6 Shtessel, Y., et al., "Sliding Mode Control and Observation, Control Engineering," Springer, 2014.
7 Edwards, C., Alwi, H. and Tan, C., 2012, "Sliding Mode Methods for Fault Detection and Fault Tolerant Control with Application to Aerospace Systems," International Journal of Applied Mathematics and Computer Science, Vol. 22, No. 1, pp. 109-124.   DOI