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Year 2023, Volume: 36 Issue: 3, 1187 - 1198, 01.09.2023

Ayça Ak Erdal Yılmaz Sevan Katrancıoğlu

https://doi.org/10.35378/gujs.979370
Cited By: 1

Abstract

References

  • [1] Wang, C., Quan, L., Jiao, Z., Zhang, S., “Nonlinear Adaptive Control of Hydraulic System with Observing and Compensating Mismatching Uncertainties”, IEEE Transactions on Control Systems Technology, 26(3): 1-12, (2017).
  • [2] Shol, G. A., Bobrow, J. E., “Experimental and simulations on the nonlinear control of a hydraulic servo system”, IEEE Transactions on Control Systems Technology, 7(1): 238–247, (1999).
  • [3] Liu, G. P., Daley, G. P., “Optimal-tuning nonlinear PID control of hydraulic systems”, Control Engineering Practice, 8(9): 1045–1053, (2000).
  • [4] Guo, K., Wei, J., Fang, J., Wang, X., “Position tracking control of electro-hydraulic single-rod actuator based on an extended disturbance observer”, Mechatronics, 27: 47-56, (2015). DOI: 10.1016/j.mechatronics.2015.02.003
  • [5] Tri, N. M., Nam, D. N. C., Park, H.G., Ahn, K. K., “Trajectory control of an electro hydraulic actuator using an iterative backstepping control scheme”, IEEE Transactions on Control Systems Technology, Mechatronics, 29: 96–102, (2015).
  • [6] Alleyne, A., Liu, R., “A simplified approach to force control for electrohydraulic systems”, Control Engineering Practice, 8(12): 1347–1356, (2000). DOI: 10.1016/S0967-0661(00)00081-2
  • [7] Yao, B., Bu, F., Chiu, G. T. C., “Nonlinear adaptive robust control of electrohydraulic servo systems with discontinuous projections”, Proceedings of the IEEE Conference on Decision and Control, Tampa (USA), 2: 2265–2270, (1998).
  • [8] Deticek E., “A fuzzy self learning position control of hydraulic drive”, Cybernetic Systems, 31 (8): 821–836, (2000). DOI: /10.1080/019697200750038959
  • [9] Kalyoncu, M., Haydim, M., “Mathematical modelling and fuzzy logic based position control of an electrohydraulic servo system with internal leakage”, Mechatronics, 19(6): 847–858, (2009). DOI: https://doi.org/10.1016/j.mechatronics.2009.04.010
  • [10] Çetin, Ş., Akkaya, A. V., “Simulation and hybrid fuzzy-PID control for positioning of a hydraulic system”, Nonlinear Dynamics, 61: 465–476, (2010).
  • [11] Knohl, T., Unbehauen H., “Adaptive position control of electrohydraulic servo systems using ANN”, Mechatronics, 10(1-2): 127–143, (2000).
  • [12] Hasanifard, G., Zarif, M.H., Ghareveisi, A.A., “Nonlinear Robust Backstepping Control of an Electrohydraulic Velocity Servosystem”, Mediterranean Conference on Control and Automation, 27-29, (2007).
  • [13] Bonchis, A., Corke, P. I., Rye D. C., Ha Q. P., “Variable structure methods in hydraulic servo systems control”, Automatica, 37(4): 589–595, (2001). DOI: 10.1007/s11771-008-0048-1
  • [14] Liu, Y., Handroos, H., “Technical note sliding mode control for a class of hydraulic position servo”, Mechatronics, 9(1): 111–123, (1999).
  • [15] Yang, L., Yang, S., Burton, R., “Modelling and robust discrete-time sliding-mode control design for a fluid power electrohydraulic actuator (EHA) system”, IEEE/ASME Transaction Mechatronics, 18(1): 1–10, (2013).
  • [16] Tang, R., Zhang, Q., “Dynamic sliding mode control scheme for electro-hydraulic position servo system”, Procedia Engineering, 24: 28–32, (2011). DOI: 10.1016/j.proeng.2011.11.2596
  • [17] Cerman, O., Petr, H., “Adaptive fuzzy sliding mode control for electro-hydraulic servo mechanism”, Expert Systems with Applications, 39(11): 10269–10277, (2012).
  • [18] Guan, C., Pan, S., “Adaptive sliding mode control of electro-hydraulic system with nonlinear unknown parameters”, Elsevier Control Engineering Practice, 16(11): 1275–1284, (2008).
  • [19] Wu, B., Dong, Y., Wu, S., Xu, D., Keding, Z., “An Integral Variable Structure Controller with Fuzzy Tuning Design for Electro-hydraulic Stewart Platform”, 1st International Symposium on Systems and Control in Aerospace and Astronautics, Harbin (China), 941-945, DOI: 10.1109/ISSCAA.2006.1627480 (2006).
  • [20] Yılmaz, E., “Modelling a Hydraulic System Using Artificial Neural Networks and Controlling with PID Algorithm Coefficients Optimized by Genetic and Particle Swarm Algorithms”, Master Thesis, Marmara University Institute of Science and Technology, Istanbul, 27-28, (2012).
  • [21] Yılmaz, E., Topuz, V., Baba, A.F., “Modeling of a Hydraulic System with ANN and Control with GA-PID and PSO-PID”, Automatic Control National Meeting, Malatya, 842-847, (2013).
  • [22] Utkin, V.I., “Variable Structure Systems with Sliding Modes”, IEEE Transaction on Automatic Control, 22(2): 212-222, (1977).
  • [23] Edwards, C., Spurgeon, K., Sliding Mode Control, First Edition, Taylor&Fransis Ltd., London, (1998).
  • [24] Bandyopadhyay, B., Kim, K., Deepak, F., Sliding Mode Control Using Novel Sliding Surfaces, First Edition, Springer-Verlag Berlin Heidelberg, Switzerland, (2009).
  • [25] Tsai, C., Chung, H., Yu, F., “Neuro-Sliding Mode Control with Its Applications to Seesaw Systems”, IEEE Transaction on Neural Networks, 15(1): 124-134, (2004).
  • [26] Kalayci, M.İ., Yiğit, İ., “Theoretical and Experimental Investigation of Some Sliding Mode Control Techniques Used in Practice”, Journal of the Faculty of Engineering and Architecture of Gazi University, 3(1): 131–142, (2015).
  • [27] Utkin, V.I., Shi, J., “Integral sliding mode in systems operating under uncertainty conditions”, Proceedings of the 35th Conference on Decision and Control, Kobe (Japan), 4591–4596, (1996).
  • [28] Zadeh, L. A., “Outline of a new approach to the analysis of complex systems and decision processes”, IEEE Transaction System Man Cybernetics, 3(1): 28–44, (1973).
  • [29] Mamdani, E.H., Assilian, S., “An experiment in linguistic synthesis with a fuzzy logic controller”, International Journal of Man-Machine Studies, 7(1): 1-13, (1975).
  • [30] Huang, S., Huang, K., Chiou, K., “Development and Application of a Novel Radial Basis Function Sliding Mode Controller”, Mechatronics, 13(4): 313–329, (2001).
  • [31] Azeem, M.F., Hanmandlu, M., Ahmad N., “Generalization of Adaptive Neuro-Fuzzy Inference Systems”, IEEE Transaction on Neural Networks, 11(6): 1332–1346, (2000).
  • [32] Ak, A., Cansever, G., Delibaşı, A., “Robot Trajectory Tracking with Adaptive RBFNN Based Fuzzy Sliding Mode Control”, Information Technology and Control, 40(2): 151–156, (2011). DOI: http://dx.doi.org/10.5755/j01.itc.40.2.430

Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling

Year 2023, Volume: 36 Issue: 3, 1187 - 1198, 01.09.2023

Ayça Ak Erdal Yılmaz Sevan Katrancıoğlu

https://doi.org/10.35378/gujs.979370
Cited By: 1

Abstract

In this paper, a hydraulic motor controller is designed with a fuzzy supported integral sliding mode algorithm. The hydraulic system used in the study was modeled using artificial neural networks. Ability of handling nonlinearity of systems makes sliding mode controller to be a good choose for this system. The integral sliding mode controller can supply the robustness the system against the uncertainties. The basic idea of the proposed control method is to use fuzzy logic for the adaptation of the integral sliding mode control switching gain. Such adjustment reduces the chattering that is the most problem of classical sliding mode control. The equivalent control is computed using the radial basis function neural network. Simulation results of the presented method were compared with conventional PID controller results. It proved that it is more efficient to control the hydraulic system with integral fuzzy sliding mode control using neural network.

Keywords

Fuzzy logic Hydraulic system Neural networks Sliding mode control

References

  • [1] Wang, C., Quan, L., Jiao, Z., Zhang, S., “Nonlinear Adaptive Control of Hydraulic System with Observing and Compensating Mismatching Uncertainties”, IEEE Transactions on Control Systems Technology, 26(3): 1-12, (2017).
  • [2] Shol, G. A., Bobrow, J. E., “Experimental and simulations on the nonlinear control of a hydraulic servo system”, IEEE Transactions on Control Systems Technology, 7(1): 238–247, (1999).
  • [3] Liu, G. P., Daley, G. P., “Optimal-tuning nonlinear PID control of hydraulic systems”, Control Engineering Practice, 8(9): 1045–1053, (2000).
  • [4] Guo, K., Wei, J., Fang, J., Wang, X., “Position tracking control of electro-hydraulic single-rod actuator based on an extended disturbance observer”, Mechatronics, 27: 47-56, (2015). DOI: 10.1016/j.mechatronics.2015.02.003
  • [5] Tri, N. M., Nam, D. N. C., Park, H.G., Ahn, K. K., “Trajectory control of an electro hydraulic actuator using an iterative backstepping control scheme”, IEEE Transactions on Control Systems Technology, Mechatronics, 29: 96–102, (2015).
  • [6] Alleyne, A., Liu, R., “A simplified approach to force control for electrohydraulic systems”, Control Engineering Practice, 8(12): 1347–1356, (2000). DOI: 10.1016/S0967-0661(00)00081-2
  • [7] Yao, B., Bu, F., Chiu, G. T. C., “Nonlinear adaptive robust control of electrohydraulic servo systems with discontinuous projections”, Proceedings of the IEEE Conference on Decision and Control, Tampa (USA), 2: 2265–2270, (1998).
  • [8] Deticek E., “A fuzzy self learning position control of hydraulic drive”, Cybernetic Systems, 31 (8): 821–836, (2000). DOI: /10.1080/019697200750038959
  • [9] Kalyoncu, M., Haydim, M., “Mathematical modelling and fuzzy logic based position control of an electrohydraulic servo system with internal leakage”, Mechatronics, 19(6): 847–858, (2009). DOI: https://doi.org/10.1016/j.mechatronics.2009.04.010
  • [10] Çetin, Ş., Akkaya, A. V., “Simulation and hybrid fuzzy-PID control for positioning of a hydraulic system”, Nonlinear Dynamics, 61: 465–476, (2010).
  • [11] Knohl, T., Unbehauen H., “Adaptive position control of electrohydraulic servo systems using ANN”, Mechatronics, 10(1-2): 127–143, (2000).
  • [12] Hasanifard, G., Zarif, M.H., Ghareveisi, A.A., “Nonlinear Robust Backstepping Control of an Electrohydraulic Velocity Servosystem”, Mediterranean Conference on Control and Automation, 27-29, (2007).
  • [13] Bonchis, A., Corke, P. I., Rye D. C., Ha Q. P., “Variable structure methods in hydraulic servo systems control”, Automatica, 37(4): 589–595, (2001). DOI: 10.1007/s11771-008-0048-1
  • [14] Liu, Y., Handroos, H., “Technical note sliding mode control for a class of hydraulic position servo”, Mechatronics, 9(1): 111–123, (1999).
  • [15] Yang, L., Yang, S., Burton, R., “Modelling and robust discrete-time sliding-mode control design for a fluid power electrohydraulic actuator (EHA) system”, IEEE/ASME Transaction Mechatronics, 18(1): 1–10, (2013).
  • [16] Tang, R., Zhang, Q., “Dynamic sliding mode control scheme for electro-hydraulic position servo system”, Procedia Engineering, 24: 28–32, (2011). DOI: 10.1016/j.proeng.2011.11.2596
  • [17] Cerman, O., Petr, H., “Adaptive fuzzy sliding mode control for electro-hydraulic servo mechanism”, Expert Systems with Applications, 39(11): 10269–10277, (2012).
  • [18] Guan, C., Pan, S., “Adaptive sliding mode control of electro-hydraulic system with nonlinear unknown parameters”, Elsevier Control Engineering Practice, 16(11): 1275–1284, (2008).
  • [19] Wu, B., Dong, Y., Wu, S., Xu, D., Keding, Z., “An Integral Variable Structure Controller with Fuzzy Tuning Design for Electro-hydraulic Stewart Platform”, 1st International Symposium on Systems and Control in Aerospace and Astronautics, Harbin (China), 941-945, DOI: 10.1109/ISSCAA.2006.1627480 (2006).
  • [20] Yılmaz, E., “Modelling a Hydraulic System Using Artificial Neural Networks and Controlling with PID Algorithm Coefficients Optimized by Genetic and Particle Swarm Algorithms”, Master Thesis, Marmara University Institute of Science and Technology, Istanbul, 27-28, (2012).
  • [21] Yılmaz, E., Topuz, V., Baba, A.F., “Modeling of a Hydraulic System with ANN and Control with GA-PID and PSO-PID”, Automatic Control National Meeting, Malatya, 842-847, (2013).
  • [22] Utkin, V.I., “Variable Structure Systems with Sliding Modes”, IEEE Transaction on Automatic Control, 22(2): 212-222, (1977).
  • [23] Edwards, C., Spurgeon, K., Sliding Mode Control, First Edition, Taylor&Fransis Ltd., London, (1998).
  • [24] Bandyopadhyay, B., Kim, K., Deepak, F., Sliding Mode Control Using Novel Sliding Surfaces, First Edition, Springer-Verlag Berlin Heidelberg, Switzerland, (2009).
  • [25] Tsai, C., Chung, H., Yu, F., “Neuro-Sliding Mode Control with Its Applications to Seesaw Systems”, IEEE Transaction on Neural Networks, 15(1): 124-134, (2004).
  • [26] Kalayci, M.İ., Yiğit, İ., “Theoretical and Experimental Investigation of Some Sliding Mode Control Techniques Used in Practice”, Journal of the Faculty of Engineering and Architecture of Gazi University, 3(1): 131–142, (2015).
  • [27] Utkin, V.I., Shi, J., “Integral sliding mode in systems operating under uncertainty conditions”, Proceedings of the 35th Conference on Decision and Control, Kobe (Japan), 4591–4596, (1996).
  • [28] Zadeh, L. A., “Outline of a new approach to the analysis of complex systems and decision processes”, IEEE Transaction System Man Cybernetics, 3(1): 28–44, (1973).
  • [29] Mamdani, E.H., Assilian, S., “An experiment in linguistic synthesis with a fuzzy logic controller”, International Journal of Man-Machine Studies, 7(1): 1-13, (1975).
  • [30] Huang, S., Huang, K., Chiou, K., “Development and Application of a Novel Radial Basis Function Sliding Mode Controller”, Mechatronics, 13(4): 313–329, (2001).
  • [31] Azeem, M.F., Hanmandlu, M., Ahmad N., “Generalization of Adaptive Neuro-Fuzzy Inference Systems”, IEEE Transaction on Neural Networks, 11(6): 1332–1346, (2000).
  • [32] Ak, A., Cansever, G., Delibaşı, A., “Robot Trajectory Tracking with Adaptive RBFNN Based Fuzzy Sliding Mode Control”, Information Technology and Control, 40(2): 151–156, (2011). DOI: http://dx.doi.org/10.5755/j01.itc.40.2.430
There are 32 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Electrical & Electronics Engineering
Authors

Ayça Ak 0000-0002-3429-4962

Erdal Yılmaz 0000-0003-4982-9357

Sevan Katrancıoğlu 0000-0002-4111-2186

Publication Date September 1, 2023
Published in Issue Year 2023 Volume: 36 Issue: 3

Cite

APA Ak, A., Yılmaz, E., & Katrancıoğlu, S. (2023). Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling. Gazi University Journal of Science, 36(3), 1187-1198. https://doi.org/10.35378/gujs.979370
AMA Ak A, Yılmaz E, Katrancıoğlu S. Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling. Gazi University Journal of Science. September 2023;36(3):1187-1198. doi:10.35378/gujs.979370
Chicago Ak, Ayça, Erdal Yılmaz, and Sevan Katrancıoğlu. “Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling”. Gazi University Journal of Science 36, no. 3 (September 2023): 1187-98. https://doi.org/10.35378/gujs.979370.
EndNote Ak A, Yılmaz E, Katrancıoğlu S (September 1, 2023) Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling. Gazi University Journal of Science 36 3 1187–1198.
IEEE A. Ak, E. Yılmaz, and S. Katrancıoğlu, “Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling”, Gazi University Journal of Science, vol. 36, no. 3, pp. 1187–1198, 2023, doi: 10.35378/gujs.979370.
ISNAD Ak, Ayça et al. “Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling”. Gazi University Journal of Science 36/3 (September 2023), 1187-1198. https://doi.org/10.35378/gujs.979370.
JAMA Ak A, Yılmaz E, Katrancıoğlu S. Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling. Gazi University Journal of Science. 2023;36:1187–1198.
MLA Ak, Ayça et al. “Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling”. Gazi University Journal of Science, vol. 36, no. 3, 2023, pp. 1187-98, doi:10.35378/gujs.979370.
Vancouver Ak A, Yılmaz E, Katrancıoğlu S. Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling. Gazi University Journal of Science. 2023;36(3):1187-98.

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