Open Access
Issue
E3S Web Conf.
Volume 207, 2020
25th Scientific Conference on Power Engineering and Power Machines (PEPM’2020)
Article Number 04003
Number of page(s) 10
Section Hydraulic and Pneumatic Fluid Power Systems and Machinery
DOI https://doi.org/10.1051/e3sconf/202020704003
Published online 18 November 2020
  1. J. Watton, The Dynamic Performance of an Electrohydraulic Servovalve/Motor System with Transmission Line Effect, Journal of Dynamic Systems, Measurement and Control, March 1987, Vol. 109, pp. 14-18 (1987) [CrossRef] [Google Scholar]
  2. T. Lieno, M. Linjama, K. Koskinen and M. Vilenius, Applicability of Laminar Flow Based Model in Pipeflow Modeling of Water Hydraulic Systems, International Journal of Fluid Power, August 2001, Vol. 2, Nr. 2, pp. 37 – 45 (2001) [CrossRef] [Google Scholar]
  3. E. Kojima, M. Shinada, J. Yu, Development Accurate and Practical Simulation Technique Based on the Modal Approximations for Fluid Transients in Compound Fluid-Line Systems, International Journal of Fluid Power, August 2002, Vol. 3, Nr. 2, pp. 5 – 13 (2002) [CrossRef] [Google Scholar]
  4. K. Ormandzhiev, T. Todorov, Numerical Method for Determination of the Dynamical Process in Pressure System of Hydro Power Station with Parallel Working Hydraulic Turbo-alternators, Research and Development in Mechanical Industry, in Proceedings, Herceg Novi, Serbia and Montenegro, 2003, Vol 3., pp.1866 – 1875 (2003) [Google Scholar]
  5. M. Saad, H. Jamaluddin, I. Darus, Implementations of PID-controller tuning using differential evolution and genetic algorithm, International Journal of Innovate Computing, Information and Control. 2012. Vol. 8, no. 11. pp. 7761-7779 (2012) [Google Scholar]
  6. Y. Sang, W. Sun, F. Duan, J. Zhao, Bidirectional synchronization control for an electrohydraulic servo loading system, October 2019, Mechatronics, (2019). [Google Scholar]
  7. H. Yanada, K. Furuta, Adaptive control of an electrohydraulic servo system utilizing online estimate of its natural frequency, Mechatronics, 2007, pp. 337-343 (2007) [Google Scholar]
  8. S. Chaudhuri, R. Saha, A. Chatterjee, S. Mookherjee, D. Sanyal, Adaptive neural-bias-sliding mode control of rugged electrohydraulic system motion by recurrent Hermite neural network, Control Engineering Practice (2020) [Google Scholar]
  9. Kalyoncu, M., M. Haydim, Mathematical modelling and fuzzy logi based position control of an electrohydraulic servosystem with internal leakage, Mechatronics, 2009, pp. 847-858 (2009) [Google Scholar]
  10. A. Schwung, M. Beck, J. Adamy, Fault diagnosis of dynamical systems using recurrent fuzzy systems with application to an electrohydraulic servo axis, Fuzzy Sets and Systems, 2015, pp. 138-153 (2015) [Google Scholar]
  11. I. Ursu, , F. Ursu, F. Popescu, Backstepping design for controlling electrohydraulic servos, Journal of the Franklin Institute, 2006, pp. 94-110 (2006) [Google Scholar]
  12. I. Davliakos, E. Papadopoulos, Impedance model-based control for an electrohydraulic Stewart platform, European Journal of Control, 2009, pp. 560-577 (2009) [Google Scholar]
  13. Q. Guo, Z. Chen, Neural adaptive control of single-rod electrohydraulic system with lumped uncertainty, Mechanical Systems and Signal Processing, Vol. 146, January 2021, 106869 (2021) [Google Scholar]
  14. P. Marusak, S. Kuntanapreeda, Constrained model predictive force control of an electrohydraulic actuator, Control Engineering Practice, Vol. 19, January 2011, pp. 62-73 (2011) [Google Scholar]
  15. Y. Chen, Y. Ma, W. Yun, Application of Improved Genetic Algorithm in PID Controller Parameters Optimization, Telkomnika, 2013, Vol. 11, no. 3, pp. 1524-1530 (2013) [Google Scholar]
  16. A. Y. Jaen-Cuellar, R. de J. Romero-Troncoso, L. Morales-Velazquez, R. A. Osornio-Rios, PID-Controller Tuning Optimization with Genetic Algorithms in Servo Systems, International Journal of Advanced Robotic Systems, 2013, Vol. 10, P. 324. DOI: 10.5772/56697 (2013) [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.