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“Iterative Learning Applied to Hydraulic Pressure Control”

Authors: Petter H. G°ytil, Michael R. Hansen and Geir Hovland,
Affiliation: University of Agder
Reference: 2018, Vol 39, No 1, pp. 1-14.

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Keywords: Hydraulic pressure control, peaking phenomenon, iterative learning control, limit cycles

Abstract: This paper addresses a performance limiting phenomenon that may occur in the pressure control of hydraulic actuators subjected to external velocity disturbances. It is demonstrated that under certain conditions a severe peaking of the control error may be observed that significantly degrades the performance of the system due to the presence of nonlinearities. The phenomenon is investigated numerically and experimentally using a system that requires pressure control of two hydraulic cylinders. It is demonstrated that the common solution of feed forwarding the velocity disturbance is not effective in reducing the peaking that occurs as a result of this phenomenon. To improve the system performance, a combination of feedback and iterative learning control (ILC) is proposed and evaluated. The operating conditions require that ILC be applied in combination with a feedback controller, however the experimental system inherently suffers from limit cycle oscillations under feedback due to the presence of valve hysteresis. For this reason the ILC is applied in combination with a feedback controller designed to eliminate limit cycle oscillations based on describing function analysis. Experimental results demonstrate the efficacy of the solution where the feedback controller successfully eliminates limit cycle oscillations and the ILC greatly reduces the peaking of the control error with reductions in the RMS and peak-to-peak amplitude of the error by factors of more than 30 and 19, respectively. Stability of the proposed solution is demonstrated analytically in the frequency domain and verified on the experimental system for long periods of continuous operation.

PDF PDF (1485 Kb)        DOI: 10.4173/mic.2018.1.1

[1] Baghestan, K., Rezaei, S., Talebi, H., and Zareinejad, M. (2014). Baghestan, K, , Rezaei, S., Talebi, H., and Zareinejad, M. Robust force control in a novel electro-hydraulic structure using polytopic uncertainty representation. ISA transactions. 53(6):1873--1880. doi:10.1016/j.isatra.2014.08.002
[2] Blanken, L., Boeren, F., Bruijnen, D., and Oomen, T. (2017). Blanken, L, , Boeren, F., Bruijnen, D., and Oomen, T. Batch-to-batch rational feedforward control: from iterative learning to identification approaches, with application to a wafer stage. IEEE/ASME Transactions on Mechatronics. 22(2):826--837. doi:10.1109/TMECH.2016.2625309
[3] Boeren, F., Bareja, A., Kok, T., and Oomen, T. (2016). Boeren, F, , Bareja, A., Kok, T., and Oomen, T. Frequency-domain ILC approach for repeating and varying tasks: With application to semiconductor bonding equipment. IEEE/ASME Transactions on Mechatronics. 21(6):2716--2727. doi:10.1109/TMECH.2016.2577139
[4] Chen, C.-K. and Zeng, W.-C. (2003). Chen, C, -K. and Zeng, W.-C. The iterative learning control for the position tracking of the hydraulic cylinder. JSME International Journal Series C Mechanical Systems, Machine Elements and Manufacturing. 46(2):720--726. doi:10.5739/isfp.2002.591
[5] Conrad, F. and Jensen, C. (1987). Conrad, F, and Jensen, C. Design of hydraulic force control systems with state estimate feedback. In Proceedings of the IFAC 10th Triennial Congress. pages 307--312. doi:10.1016/S1474-6670(17)55388-4
[6] Daley, S., Hatonen, J., and Owens, D. (2004). Daley, S, , Hatonen, J., and Owens, D. Hydraulic servo system command shaping using iterative learning control. In Proc. of the Control Conf. pages 117--121. doi:10.1049/ic:20040657
[7] Esfandiari, M. and Sepehri, N. (2014). Esfandiari, M, and Sepehri, N. On high bandwidth output pressure control design of hydraulic actuators using quantitative feedback theory. Transactions of the Canadian Society for Mechanical Engineering. 38(4):533--555. doi:10.1631/FITEE.1601104
[8] Franklin, G.F., Powell, J.D., and Abbas, E.-N. (2015). Franklin, G, F., Powell, J.D., and Abbas, E.-N. Feedback control of dynamic systems. Pearson. .
[9] Goytil, P.H. (2017). Goytil, P, H. Closed-Loop Electrohydraulic Pressure Control. University of Agder, MSc thesis. .
[10] Horowitz, I. (1963). Horowitz, I, Synthesis of Feedback Systems. Academic Press. .
[11] Jiao, Z.-X., Gao, J.-X., Qing, H., and Wang, S.-P. (2004). Jiao, Z, -X., Gao, J.-X., Qing, H., and Wang, S.-P. The velocity synchronizing control on the electro-hydraulic load simulator. Chinese journal of aeronautics. 17(1):39--46. doi:10.1016/S1000-9361(11)60201-X
[12] Klausen, A. and Tordal, S.S. (2015). Klausen, A, and Tordal, S.S. System Identification of a Variable Piston Pump and Design of a Hydraulic Load Circuit. University of Agder, MSc thesis. .
[13] Lamming, C., Plummer, A.R., and Hillis, A.J. (2010). Lamming, C, , Plummer, A.R., and Hillis, A.J. Analysis of robust electrohydraulic force control. In 7th International Fluid Power Conference. Achen, Germany, 2010. .
[14] Ledezma, J.A., DeNegri, V.J., and DePieri, E.R. (2015). Ledezma, J, A., DeNegri, V.J., and DePieri, E.R. New approach for hydraulic force control based on hydraulic compliance. In International Conference on Fluid Power and Mechatronics. pages 454--459. doi:10.1109/FPM.2015.7337160
[15] Lingjun, L., Poms, U., and Thurner, T. (2014). Lingjun, L, , Poms, U., and Thurner, T. Accurate position control of a servo-hydraulic test cylinder by iterative learning control technique. In European Modelling Symposium. pages 297--302. doi:10.1109/EMS.2014.87
[16] Longman, R.W. (2000). Longman, R, W. Iterative learning control and repetitive control for engineering practice. International journal of control. 73(10):930--954. doi:10.1080/002071700405905
[17] Lurie, B.J. and Enright, P.J. (2012). Lurie, B, J. and Enright, P.J. Classical feedback control: with matlab and simulink. CRC Press. .
[18] Merritt, H.E. (1967). Merritt, H, E. Hydraulic control systems. John Wiley & Sons Inc.. .
[19] Mougenet, F. and Hayward, V. (1995). Mougenet, F, and Hayward, V. Limit cycle characterization, existence and quenching in the control of a high performance hydraulic actuator. In IEEE Int. Conf. Robot. Automat., volume3. pages 2218--2223. doi:10.1109/ROBOT.1995.525591
[20] Norrloef, M. (2000). Norrloef, M, Iterative Learning Control: Analysis, Design, and Experiments. Linkoeping University, PhD thesis. .
[21] Ottestad, M., Nilsen, N., and Hansen, M.R. (2012). Ottestad, M, , Nilsen, N., and Hansen, M.R. Reducing the static friction in hydraulic cylinders by maintaining relative velocity between piston and cylinder. In 12th International Conference on Control, Automation and Systems. pages 764--769. .
[22] Wallen, J. (2011). Wallen, J, Estimation-based iterative learning control. Linkoeping University, PhD thesis. .
[23] Wang, S.-k., Zhao, J.-b., and Wang, J.-z. (2015). Wang, S, -k., Zhao, J.-b., and Wang, J.-z. Open-closed-loop iterative learning control for hydraulically driven fatigue test machine of insulators. Journal of Vibration and Control. 21(12):2291--2305. doi:10.1177/1077546313508998
[24] Zhao, J., French, C., Shield, C., and Posberg, T. (2004). Zhao, J, , French, C., Shield, C., and Posberg, T. Effective force testing with nonlinear velocity feedback compensation. In 13th World Conference on Earthquake Engineering. Vancouver, Canada. .
[25] Zhao, S., Wang, J., Wang, L., Hua, C., and He, Y. (2005). Zhao, S, , Wang, J., Wang, L., Hua, C., and He, Y. Iterative learning control of electro-hydraulic proportional feeding system in slotting machine for metal bar cropping. International Journal of Machine Tools and Manufacture. 45(7):923--931. doi:10.1016/j.ijmachtools.2004.10.013

  title={{Iterative Learning Applied to Hydraulic Pressure Control}},
  author={G°ytil, Petter H. and Hansen, Michael R. and Hovland, Geir},
  journal={Modeling, Identification and Control},
  publisher={Norwegian Society of Automatic Control}


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