Time-delay estimator and disturbance observer based on neural network in networked control system
Keywords:disturbance observer, networked control system, neural network, Smith predictor, time-delay estimator
In this paper, we deal with the control problem of network induced delays and randomly varying time-delay controlled plant under the effect of disturbances and noise in networked control systems (NCS). In a time-delay NCS it becomes more challenging to attain stability when the disturbances and noise interference appear in form of a time-varying signal in the close loop of the NCS. These in turn make the conventional control methods, e.g., normal mathematical model of Smith predictor, more complicated when the aim is to meet quality requirements of the NCS. To overcome these inherent challenges, we mainly analyze the existing techniques, and then propose a novel method to efﬁciently reduce the effect of time-delays, disturbances, and noise interference for highly efﬁcient and accurate control purposes. Speciﬁcally, we introduce a joint solution of time-delay estimator and disturbance observer in which the outer loop with an adaptive Smith predictor is utilized to compensate time-delays for the whole NCS while the inner loop with disturbance observer is to eliminate the disturbances and noise interference. By using neural network identiﬁcation and the estimation method, the proposed model provides many outstanding advantages such as high adaptation, robust stability, and fast response. The simulation results generated via TrueTime Beta2.0 platform demonstrate that our design signiﬁcantly improves the performance of NCS.
Agarwal, M., & Canudas, C. (1987). On-line estimation of time delay and continuous-time process parameters. International Journal of Control, 46(1), 295-311. http://dx.doi.org/10.1080/00207178708933899
Anton, C., Henriksson, D., & Martin, O. (2009). TrueTime 2.0 beta 1 - Reference Manual, 1st ed. Sweden: Department of Automatic Control, Lund University.
Bahill, A. T. (1983). A simple adaptive Smith-predictor for controlling ime-delay systems. IEEE. Control System Magazine, 3(2), 16-22. DOI: 10.1109/MCS.1983.1104748
Chiang, W. L., Chen, T. W., Liu, M. Y, & Hsu, C. J. (2001). Application and robust H∞ control of PDC fuzzy controller for nonlinear systems with external disturbance. Journal of Marine Science and Technology, 9(2), 84-90. http://jmst.ntou.edu.tw/marine/9-2/84-90.pdf
Choi, Y., Yang, K., Chung, W. K., Kim, H. R., & Suh, I. H. (2003). On the robustness and performance of disturbance observers for second-order systems. IEEE Transactions on Automatic Control,48(2), 315-320. DOI: 10.1109/TAC.2002.808491
Cuenca, A., García, P., Albertos, P., & Salt, J. (2011). A non-uniform predictor-observer for a networked control system. International Journal of Control, Automation, and Systems, 9(6), 1194-1202. DOI 10.1007/s12555-011-0621-5
Cuenca, A., Salt, J. Casanova, V., & Pizá, R. (2010). An approach based on an adaptive multi-rate smith predictor and gain scheduling for a networked control system: Implementation over Proﬁbus - DP. International Journal of Control, Automation, and Systems, 8(2), 473-481. DOI: 10.1007/s12555-010-0237-1
Dang, X. K., Guan, Z. H., Li, T., & Zhang, D. X. (2012). Joint smith predictor and neural network estimation scheme for compensating randomly varying time-delay in networked control system. Proceedings of the 24th Chinese Control and Decision Conference, China, 512-517. DOI: 10.1109/CCDC.2012.6244077
Dang, X. K., Guan, Z. H., Tran H. D., & Li, T. (2011). Fuzzy adaptive control of networked control system with unknown time-delay. Proceedings of the 30th Chinese Control Conference, China, 4622-4626. DOI: 10.1109/ICMLC.2008.4620729
Dang, X. K., Nguyen, V. T., & Nguyen, X. P. (2015). Robust control of networked control systems with randomly varying time-delays based on adaptive Smith predictor. Rangsit Journal of Arts and Sciences, 5(2), 175-186. DOI: 10.14456/rjas.2015.16
Gao, Z., & Ding, S. X. (2007). State and disturbance estimator for time-delay systems with application to fault estimation and signal compensation. IEEE Transactions on Signal Processing, 55(12), 5541-5551. Doi: 10.1109/TSP.2007.900154
Grieco, L. A., & Mascolo, S. (2002). Smith predictor and feed forward disturbance compensation for ATM congestion control. Proceedings of the 41th IEEE Conf. Decision and Control, USA, 987-992. DOI: 10.1109/CDC.2002.1184638
Huang, Y. J. ., Kuo, T. C., & Tseng, H. Y. (2007). Fuzzy estimator design for the control systems with unknown time-delay. Proceedings of the World Congress on Engineering, 417- 420.
Kato, A., Muis, A., & Ohnishi, K. (2006). Robust network motion control system based on disturbance observer. Automatika, 47(1-2), 5-10.
Kaya, I. (2003). A new Smith predictor for controlling a process with an integrator and long dead-time. ISA Transactions, 42, 101-110.
Kenji, N., & Kouhei, O. (2008). A design method of communication disturbance observer for time delay compensation, taking the dynamic property of network disturbance into account. IEEE Transactions on Industrial Electronics, 55(5), 2152-2168. DOI: 10.1109/TIE.2008.918635
Koofigar, H. R. (2014). Robust adaptive control with environmental disturbance rejection for perturbed underwater vehicles. Journal of Marine Science and Technology, 22(4), 455-462. DOI: 10.6119/JMST-013-0522-3
Lai, C. L., & Hsu, P. L. (2010). Design the remote control system with the time-delay estimator and the adaptive Smith predictor. IEEE Transactions on Industrial Informatics, 6(1), 73-80. DOI: 10.1109/TII.2009.2037917
Lee, M. H., Park, H. G., Lee, W. B., Lee, K. S., Jeong, W. B., Yoon, K. S., . . . Choi, K. K. (2012). On the design of a disturbance observer for moving target tracking of an autonomous surveillance robot. International Journal of Control, Automation, and Systems, 10(1), 117-125. DOI 10.1007/s12555-012-0113-2
Na, J., Castello, R. C. N. R., Grino, & Ren, X. M. (2009). Disturbance observer based repetitive controller for time-delay systems. Proceedings of IEEE Conference on Emerging Technologies & Factory Automation, Spain, 1-9. DOI: 10.1109/ETFA.2009.5347008
Shaltaf, S., & Abdallah, M. (2000). An enhanced technique for online discrete cosine transform based time varying delay estimation. Circuits Systems and Signal Processing, 19(6), 501-515. DOI: 10.1007/BF01271285
Shaltaf, S. J., & Mohammad, A. A. (2009). Neural networks based time-delay estimation using DCT coefﬁcients. American Journal of Applied Sciences, 6(4), 703-708. DOI: 10.3844/ajassp.2009.703.708
Shaltaf, S. J. (2007). Neuro-fuzzy based time-delay estimation using DCT coefﬁcients. ISA Transactions, 46(1), 21-30. DOI: 10.1016/j.isatra.2006.02.002
Shima, H., & Jo, N. H. (2009). An almost necessary and sufﬁcient condition for robust stability of closed-loop systems with disturbance observer. Automatica, 45(1), 296-299. DOI: 10.1016/j.automatica.2008.10.009
Tran, H. D., Guan, Z. H., Dang, X. K., Cheng, X. M., & Yuan, F. S (2013). A normalized PID controller in networked control systems with varying time delays. ISA Transactions, 52(5), 592-599. DOI: 10.1016/j.isatra.2013.05.005
Yang, K. j., Choi, Y. j., Chung, W. K., Suh, I. H., & Oh, S. R. (2002). Robust tracking control of optical disk drive system using error based disturbance observer and its performance measure. Proceedings of the American Control Conference, USA, 2, 1395-1400. DOI: 10.1109/ACC.2002.1023216
Yashiro, D., & Kouhei, O. (2010). A Communication disturbance observer with a band-pass filter for delay time compensation. IEEE International Symposium on Industrial Electronics, 3585 - 3589. DOI: 10.1109/ISIE.2010.5637330
Yoo, S. J., Park, J. B., & Choi, Y. H. (2009). Adaptive dynamic surface control for disturbance attenuation of nonlinear systems, International Journal of Control, Automation, and Systems, 7(6), 882-887. DOI: 10.1007/s12555-009-0602-0
Zhao, G., & Wang, J. (2011). H∞ DOF control of stochastic systems with time-varying delay and L∞ disturbance. International Journal of Control, Automation, and Systems, 9(4), 777-784. DOI: 10.1007/s12555-011-0420-z
Zhong, Q. C., & Normey-Rico, J. E. (2001). Disturbance observer based control for processes with an integrator and long dead-time. Proceedings of the 40th IEEE Conference on Decision and Control, USA, 3, 2261-2266. DOI: 10.1109/.2001.980594
How to Cite
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.