Browse > Article
http://dx.doi.org/10.22680/kasa2021.13.4.129

Actuator Fault Detection and Adaptive Fault-Tolerant Control Algorithms Using Performance Index and Human-Like Learning for Longitudinal Autonomous Driving  

Oh, Sechan (한경대학교 ICT로봇기계공학부)
Lee, Jongmin (서울대학교 기계항공공학부)
Oh, Kwangseok (한경대학교 ICT로봇기계공학부)
Yi, Kyongsu (서울대학교 기계항공공학부)
Publication Information
Journal of Auto-vehicle Safety Association / v.13, no.4, 2021 , pp. 129-143 More about this Journal
Abstract
This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.
Keywords
Feedback control; Autonomous driving; Multiple RLS; Fault tolerant control; Performance index;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Abci, B., El Najjar, M. E. B. and Cocquempot, V., 2019, "Sensor and actuator fault diagnosis for a multi-robot system based on the Kullback-Leibler Divergence", 2019 4th Conference on Control and Fault Tolerant Systems (SysTol) IEEE, pp. 68~73.
2 Kamakar, S., Chattopadhyay, S. Mitra, M. and Sengupta, S., 2016, "Induction motor fault diagnosis: approach through current signature analysis", Springer.
3 Jeon, N. and Lee, H., 2016, "Integrated fault diagnosis algorithm for motor sensor of in-wheel independent drive electric vehicles", Sensors, Vol. 16, No. 12, pp. 2106.   DOI
4 Kommuri, S. K., Defoort, M., Karimi, H. R. and Veluvolu, K. C., 2016, "A robust observer-based sensor fault-tolerant control for PMSM in electric vehicles", IEEE Transactions on Industrial Electronic, Vol. 63, No. 12, pp. 7671~7681.   DOI
5 Abci, B., El Najjar, M. E. B., Cocquempot, V. and Dherbomez, G., 2020, "An informational approach for sensor and actuator fault diagnosis for autonomous mobile robots", Journal of Intellignet & Robotic Systems, Vol. 99, No. 2, pp. 387~406.   DOI
6 Realpe, M., Vintimilla, B. and Vlacic, L., 2015, "Sensor fault detection and diagnosis for autonomous vehicles", MATEC Web of Conferences, Vol. 30, No. 04003, pp. 1~6.
7 Edwards, C., Alwi, H. and Tan, C. P., 2010, "Sliding mode methods for fault detection and fault tolerant control", 2010 Conference on Control and Fault- Tolerant Systems (SysTol), IEEE, pp. 106~117.
8 O'Doherty, J. P., Lee, S. W. and McNamee, D., 2015, "The structure of reinforcement-learning mechanisms in the human brain", Current Opinion in Behavioral Sciences, Vol. 1, No. 2, pp. 94~100.   DOI
9 Mekki, H., Benzineb, O., Tadjine, M. and Benbouzid, M., 2015, "Sliding mode based fault detection, reconstruction and fault tolerant control scheme for motor systems", ISA transactions, Vol. 57, No. 7, pp. 340~351.   DOI
10 Tran, M. K. and Fowler, M., 2020, "Sensor fault detection and isolation for degrading lithium-ion batteries in electric vehicles using parameter estimation with recursive least squares", Batteries, Vol. 6, No. 1, pp. 1~16.   DOI
11 Karras, G. C. and Fourlas, G. K., 2020, "Model predictive fault tolerant control for omni-directional mobile robots", Journal of Intelligent & Robotics Systems, Vol. 97, No. 5, pp. 635~655.   DOI
12 Zhang, X., Xie, Y., Jiang, L., Li, G., Meng J. and Huang, Y., 2019, "Fault-tolerant dynamic control of a four-wheel redundantly-actuated mobile robot", IEEE Access, Vol. 7, pp. 157909~157921.   DOI
13 Boukhari, M. R., Chaibet, A., Boukhnifer, M. and Glaser, S., 2016, "Sensor fault tolerant control strategy for autonomous vehicle driving", 2016 13th International Multi-Conference on Systems, Signal & Devices (SSD), IEEE, pp. 241~248.
14 Fourlas, G. K., Karras, G. C. and Kyriakopoulos, K. J., 2015, "Sensors fault diagnosis in autonomous mobile robots using observer-Based technique", 2015 International Conference on Control, Automation and Robotics, IEEE, pp. 49~54.
15 Jeong, Y., Kim, K., Kim, B., Yoon, J., Chong, H., Ko, B. and Yi, K., 2015, "Vehicle sensor and actuator fault detection algorithm for automated vehicles", 2015 IEEE Intelligent Vehicles Symposium (IV), IEEE, pp. 927~932.
16 Boukhari, M. R., Chaibet, A., Boukhnifer, M. and Glaser, S., 2018, "Proprioceptive sensors' fault tolerant control strategy for an autonomous vehicle", Sensors, Vol. 18, No. 6, pp. 1893~1917.   DOI