Adaptive-Smith Predictor for Controlling an Automotive Electronic Throttle over Network


The paper presents a control strategy for an automotive electronic throttle, a device used to regulate the power produced by spark-ignition engines. Controlling the electronic throttle body is a difficult task because the throttle accounts strong nonlinearities. The difficulty increases when the control works through communication networks subject to random delay. In this paper, we revisit the Smith-predictor control, and show how to adapt it for controlling the electronic throttle body over a delay-driven network. Experiments were carried out in a laboratory, and the corresponding data indicate the benefits of our approach for applications.


[1] Astrom, K.J.; Hagglund, T. (2004); Revisiting the Ziegler-Nichols step response method for PID control, Journal of Process Control, 14, 635–650, 2004.

[2] Balau, A.E.; Caruntu, C.F.; Lazar, C.(2011); Simulation and control of an electro-hydraulic actuated clutch, Mechanical Systems and Signal Processing, 25, 1911–1922, 2011.

[3] Caruntu, C.F.; Lazar, C. (2014); Network delay predictive compensation based on timedelay modeling as disturbance. International Journal of Control, 87, 2012–2026, 2014.

[4] Caruntu, C.F.; Lazar, M.; Gielen, R.H.; van den Bosch, P.P.J.; Di Cairano, S. (2013); Lyapunov based predictive control of vehicle drivetrains over CAN, Control Engineering Practice, 21, 1884–1898, 2013.

[5] Chen, C.H.; Lin, C.L.; Hwang, T.S.(2007); Stability of networked control systems with time-varying delays, IEEE Communication Letters, 11, 270–272, 2007.

[6] Deur, J.; Pavkovic, D.; Peric, N.; Jansz, M.; Hrovat, D.(2004); An electronic throttle control strategy including compensation of friction and limp-home effects, IEEE Transactions on Industry Applications, 40, 821–834, 2004.

[7] di Bernardo, M.; di Gaeta, A.; Montanaro, U.; Olm, J.M.; Santini, S.(2013); Experimental validation of the discrete-time MCS adaptive strategy, Control Engineering Practice, 21, 847–859, 2013.

[8] Jiao, X.; Zhang, J.; Shen, T. (2014); An adaptive servo control strategy for automotive electronic throttle and experimental validation, IEEE Transactions on Industrial Electronics, 61, 6275–6284, 2014.

[9] Kim, D.; Peng, H.; Bai, S.; Maguire, J.M. (2007); Control of integrated powertrain with electronic throttle and automatic transmission, IEEE Transactions on Control Systems Technology, 15, 474–482, 2007.

[10] 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, 73–80, 2010.

[11] Lee, K.C.; Kim, M.H.; Lee, S.; Lee, H.H. (2004); IEEE-1451-Based smart module for invehicle networking systems of intelligent vehicles, IEEE Transactions on Industrial Electronics, 51, 1150–1158, 2004.

[12] Li, Y.; Yang, B.; Zheng, T.; Li, Y.; Cui, M.; Peeta, S. (2015); Extended-state-observer-based double-loop integral sliding-mode control of IEEE Transactions on Intelligent Transportation Systems, 16, 2501–2510, 2015.

[13] Mahmoud, M.S.(2014); Control and Estimation Methods over Communication Networks, Springer International Publishing Switzerland, 2014.

[14] Montanaro, U.; di Gaeta, A.; Giglio, V. (2014); Robust discrete-time MRAC with minimal controller synthesis of an electronic throttle body, IEEE/ASME Transactions on Mechatronics, 19, 524–537, 2014.

[15] Natori, K.; Oboe, R.; Ohnishi, K. (2008); Stability analysis and practical design procedure of time delayed control systems with communication disturbance observer, IEEE Transactions on Industrial Informatics, 4, 185–197, 2008.

[16] Natori, K.; Ohnishi, K. (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, 2152–2168, 2008.

[17] Navet, N.; Song, Y.; Simonot-Lion, F.; Wilwert, C. (2005); Trends in automotive communication systems, Proceedings of the IEEE, 93, 1204–1223, 2005.

[18] Normey-Rico, J.E.; Camacho, E.F. (2007); Control of dead-time processes, Advanced Textbooks in Control and Signal Processing, Springer-Verlag London, 2007.

[19] de Oliveira Souza, F.; Mozelli, L.A.; de Oliveira, M.C.; Palhares, R.M. (2016); LMI International Journal of Control, 89(10), 1962–1971, 2016.

[20] Pan, Y.; Ozguner, U.; Dagci, O.H. (2008); Variable-structure control of electronic throttle valve, IEEE Transactions on Industrial Electronics, 55, 3899–3907, 2008.

[21] Panzani, G.; Corno, M.; Savaresi, S.M. (2013); On adaptive electronic throttle control for sport motorcycles, Control Engineering Practice, 21(1), 42 – 53, 2013.

[22] Pavkovic, D.; Deur, J.; Janszb, M.; Peric, N. (2006); Adaptive control of Control Engineering Practice, 14(2), 121 – 136, 2006.

[23] Podivilova, E.; Vargas, A.N.; Shiryaev, V.; Acho, L. (2016); Set-valued estimation of switching linear system: an application to an automotive throttle valve, International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 29(4), 755–762, 2016.

[24] Pujol, G.; Vidal, Y.; Acho, L.; Vargas, A.N. (2016); Asymmetric modelling and control of an electronic throttle, International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 29, 192–204, 2016.

[25] Repele, L.; Muradore, R.; Quaglia, D.; Fiorini, P. (2014); Improving performance of networked control systems by using adaptive buffering, IEEE Transactions on Industrial Electronics, 61, 4847–4856, 2014.

[26] Rossi, C.; Tilli, A.; Tonielli, A. (2000); Robust control of a throttle body for drive by wire operation of automotive engines, IEEE Trans. Control Syst. Technol., 8(6), 993 –1002, 2000.

[27] Sarkar, B.; Chakrabarti, A.; Ananthasuresh, G.K. (2017); Synthesis of feedback-based design concepts for sensors, Research in Engineering Design, 131–151, 2017.

[28] Vargas, A.N.; Menegaz, H.M.T.; Ishihara, J.Y.; Acho, L.: (2016); Unscented Kalman filters for estimating the position of an automotive electronic throttle valve, IEEE Transactions on Vehicular Technology, 65(6), 4627–4632, 2016.

[29] Vasak, M.; Baotic, M.; Petrovic, I.; Peric, N. (2007); Hybrid theory-based time-optimal control of an electronic throttle, IEEE Transactions on Industrial Electronics, 54, 1483– 1494, 2007.

[30] Yuan, X.; Wang, Y. (2009); A novel electronic-throttle-valve controller based on approximate model method, IEEE Trans. Industrial Electronics, 56(3), 883–890, 2009.

[31] Zhang, S.; Yang, J.J.; Zhu, G.G. (2015); LPV modeling and mixed constrained H2=H1 control of an electronic throttle, IEEE/ASME Transactions on Mechatronics, 20, 2120– 2132, 2015.
How to Cite
CARUNTU, Constantin et al. Adaptive-Smith Predictor for Controlling an Automotive Electronic Throttle over Network. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 13, n. 2, p. 151-161, apr. 2018. ISSN 1841-9844. Available at: <>. Date accessed: 09 aug. 2020. doi:


Adaptive-Smith predictor, electronic throttle control, networked control systems, switching control