Fault Detection of Robot Control Systems Based on Available Wireless Network Measurements


Article Preview

Considering some robot control systems which employ wireless networks to transmit sensor signals between the controller and the nonlinear controlled object, the fault detection is carried out. Firstly, based on T-S fuzzy model, the object is linearized. The fuzzy observer is designed and the error equation of the observer is given by using the fuzzy dominant subsystem rule. Secondly, the error equation is equal to the discrete switched system related to the hop count of the wireless transmission, and the stability of the error system is proved. Finally, a simulation example is given to demonstrate the effectiveness of the proposed method in this paper.



Edited by:

Ching Kuo Wang and Jing Guo




J. Zhang et al., "Fault Detection of Robot Control Systems Based on Available Wireless Network Measurements", Applied Mechanics and Materials, Vols. 300-301, pp. 604-610, 2013

Online since:

February 2013




[1] Bansode R S, Patil S R, Rathi S. A cross-layer approach for wireless networked control system with better channel coding scheme[A]. Proceedings of the International Conference on Emerging Trends in Technology[C]. New York, USA: ACM Press , 2011: 1020-1023.

DOI: https://doi.org/10.1145/1980022.1980244

[2] Taylor J H, Ibrahim H M S. Proposal and communication scheme for a wireless networked control system coordination agent[A]. Proceedings of the International Conference on Cyber-Physical Systems[C].Stockholm, Sweden: Citeseer Press, 2010: 12-16.

[3] Ajit Ambike, Won-jong Kim, Kun Ji. Real-time operating environment for networked control systems [A]. Proceeding of the 2005 American control conference [C], Portland, USA, 2005. 2353-2358.

DOI: https://doi.org/10.1109/acc.2005.1470318

[4] Wang Changhong, Wang Yufeng, Ma Guangcheng. Compensation time-varying delays in networked control systems via jump linear system approach [A]. Proceeding of the 5th World Congress on Intelligent Control and Automation [C], Hangzhou, P.R. China, 2004. 1343-1347.

DOI: https://doi.org/10.1109/wcica.2004.1340859

[5] Yu Mei, Wang Long, Chu Tianguang, Hao Fei. An LMI approach to networked control systems with data packet dropout and transmission delays [A]. Proceeding of the 43rd IEEE Conference on Decision and Control [C], Atlantis, Paradise Island, Bahamas, 2004. 14-17.

DOI: https://doi.org/10.1109/cdc.2004.1429262

[6] Hao Ye and S.X. Ding, Fault detection of networked control systems with network-induced delay, 8th International Conference on Control, Automation, Robotics and Vision. Kuming, China, 2004. 294-297.

DOI: https://doi.org/10.1109/icarcv.2004.1468840

[7] Zheng Ying, Fang Huangjing and Wang Yanwei. Kalman filter based FDI of networked control system, Proceeding of 5th World Congress on Intelligent Control and Automation. Hangzhou, China, 2004. 1330-1333.

DOI: https://doi.org/10.1109/wcica.2004.1340856

[8] Zhang W. Stability Analysis of Networked Control System[D]. Cleveland, Ohio, USA. Case Western Reserve University. (2001).

[9] Bao Yong, Dai Qiu-qiu and Cui Ying-liu, et al. Fault detection based on robust states observer on networked control systems [C]/2005 International Conference on Control and Automation, Budapest, Hungary, 2005, 1237-1241.

DOI: https://doi.org/10.1109/icca.2005.1528310

[10] Peng Li-ping, Yue Dong. Research of wireless networked control systems[J]. Control Engineering of China, 2006, 13(5): 481-484.

[11] Peng Li-ping. Controller design and simulation of wireless networked control systems[D]. Nanjing Normal University. (2007).

[12] Sun Zeng-qi, Zhang Zai-xing, Deng Zhi-dong. Intelligent control theory and technology[M]. Beijing: Tsinghua University Press, (1997).