Research Paper:
Designing an Axial Piston Pump Displacement Controller for Varying Reference Trajectory Based on Model Predictive Control
Tsuyoshi Yamada and Kazuhisa Ito

Shibaura Institute of Technology
307 Fukasaku, Minuma-ku, Saitama, Saitama 337-8570, Japan
Corresponding author
Variable displacement hydraulic pumps are applied to a wide range of fields for energy saving, but the displacement control is easily influenced by changes in dynamic characteristics depending on the operating point, and the control valve and pump displacement have constraints. Therefore, high control performance cannot be obtained without considering these nonlinearities. In a previous study, we designed a pump displacement control system based on a model predictive control (MPC) method that can consider various constraints at the design step. However, the previously presented control system requires the pre-designed reference trajectory of the pump displacement at the design step. Furthermore, the pump displacement cannot track to other reference trajectories. In this study, an extended MPC proposed in a previous study is combined with an adaptive model matching-based MPC with an inverse optimization method, proposed as a control system by the authors. This compensates for modeling errors and optimizes the weights of the evaluation function to achieve tracking to arbitrary time-varying reference trajectories using a virtual reference signal. To improve tracking performance, variable control input constraints, which are also proposed in our previous study, are introduced. The tracking performance of this control system for arbitrary time-varying reference trajectories have been verified by experiments. The experimental results have shown that the proposed control system achieves high tracking accuracy for an arbitrary time-varying reference trajectory and significantly reduces the man-hours for the parameter design of the control system.
- [1] A. Beddoti, F. Campanini, M. Pastori, L. Ricco, and P. Cassoli, “Energy saving solutions for a hydraulic excavator,” Energy Procedia, Vol.126, pp. 1099-1106, 2017. https://doi.org/10.1016/j.egypro.2017.08.255
- [2] L. Ge, X. Zhang, and J. Yang, “Power matching and energy efficiency improvement of hydraulic excavator driven with speed and displacement variable power source,” Chinese J. of Mechanical Engineering, Vol.32, Article No.100, 2019. https://doi.org/10.1186/s10033-019-0415-x
- [3] L. V. Larsson and P. Krus, “Displacement control strategies of an in-line axial-piston unit,” Proc. of 15th Scandinavian Int. Conf. on Fluid Power, pp. 244-253, 2017. https://doi.org/10.3384/ecp17144244
- [4] Y. Song, D. Wang, H. Ren, J.-C. Cai, and B. Jing, “Research on hydraulic pump displacement control using PI and feed-forward compensation,” Advances in Mechanical Engineering, Vol.9, No.12, 2017. https://doi.org/10.1177/1687814017744087
- [5] W. Kemmetmuller, F. Fuchshumer, and A. Kugi, “Nonlinear pressure control of self-supplied variable displacement axial piston pumps,” Control Engineering Practice, Vol.18, No.1, pp. 84-93, 2010. https://doi.org/10.1016/j.conengprac.2009.09.006
- [6] T.-V. Vu, C.-K. Chen, and C.-W. Hung, “A model predictive control approach for fuel economy improvement of a series hydraulic hybrid vehicle,” Energies, Vol.7, Issue 11, pp. 7014-7040, 2014. https://doi.org/10.3390/en7117017
- [7] W. Gu, Z. Yao, and J. Zheng, “Output feedback model predictive control of hydraulic systems with disturbances compensation,” ISA Trans., Vol.88, pp. 216-224, 2019. https://doi.org/10.1016/j.isatra.2018.12.007
- [8] P. Zeman, W. Kemmetmuller, and A. Kugi, “Model predictive speed control of axial piston motors,” IFAC Papers Online, Vol.49, Issue 18, pp. 772-777, 2016. https://doi.org/10.1016/j.ifacol.2016.10.259
- [9] A. Mitov, J. Kralev, T. Slavov, and I. Angelov, “Comparison of model predictive control (MPC) and linear-quadratic Gaussian (LQG) algorithm for electrohydraulic steering control system,” 25th Scientific Conf. on Power Engineering and Power Machines, Vol.207, 2020. https://doi.org/10.1051/e3sconf/202020704001
- [10] A. Bozza, B. Askari, G. Cavone, R. Carli, and M. Dotoli, “An adaptive model predictive control approach for position tracking and force control of a hydraulic actuator,” 2022 IEEE 18th Int. Conf. on Automation Science and Engineering, pp. 2019-1034, 2022. https://doi.org/10.1109/CASE49997.2022.9926645
- [11] V. Verma, S. Kumar, and A. Anand, “Dynamic speed control of axial piston pump using adaptive model predictive control with Kalman filter,” 2024 Int. Conf. on Signal Processing and Advance Research in Computing, 2024. https://doi.org/10.1109/SPARC61891.2024.10829339
- [12] S. D. Cairano and A. Bemporad, “Model predictive control tuning by controller matching,” IEEE Trans. on Automatic Control, Vol.55, Issue 1, pp. 185-190, 2010. https://doi.org/10.1109/TAC.2009.2033838
- [13] S. Tsuruhara, R. Inada, and K. Ito, “Model predictive displacement control tuning for tap-water-driven artificial muscle by inverse optimization with adaptive model matching and its contribution analyses,” Int. J. Automation Technol., Vol.16, No.4, pp. 436-447, 2022. https://doi.org/10.20965/ijat.2022.p0436
- [14] T. Yamada, R. Inada, and K. Ito, “Designing a model predictive controller for displacement control of axial piston pump,” Int. J. Automation Technol., Vol.18, No.1, pp. 113-127, 2024. https://doi.org/10.20965/ijat.2024.p0113
- [15] N. Wada and S. Tsurushima, “Constrained MPC to track time-varying references signal: Online optimization of virtual reference signal and controller states,” IEEJ Trans. on Electrical and Electric Engineering, Vol.11, Issue S2, pp. S65-S74, 2016. https://doi.org/10.1002/tee.22337
- [16] J. Grabbel and M. Ivantysynova, “An investigation of swash plate control concepts for displacement controlled actuators,” Int. J. of Fluid Power, Vol.6, No.2, pp. 19-36, 2014. https://doi.org/10.1080/14399776.2005.10781217
- [17] K. Guo, Y. Xu, and J. Li, “A switched controller design for supply pressure tracking of variable displacement axial piston pumps,” IEEE Access, Vol.6, pp. 3932-3942, 2018. https://doi.org/10.1109/ACCESS.2018.2796097
- [18] T. Yamada, K. Ito, and R. Inada, “Parameter design of model predictive control for the displacement control of an axial piston pump,” 9th Int. Conf. on Fluid Power and Mechatronics (FPM), 2023. https://doi.org/10.1109/FPM57590.2023.10565546
- [19] N. M. Linh, T. V. Minh, and X. Chen, “Precise tracking control for piezo-actuated stage using inverse compensation and model predictive control,” 2015 Int. Conf. on Advanced Mechatronic Systems, pp. 467-472, 2015. https://doi.org/10.1109/ICAMechS.2015.7287156
- [20] N. Wada, “Model predictive tracking control for constrained linear systems using integrator resets,” IEEE Trans. on Automatic Control, Vol.60, Issue 11, pp. 3113-3118, 2015. https://doi.org/10.1109/TAC.2015.2411915
- [21] R. Mantri, A. Saberi, Z. Lin, and A. A. Stroorvogel, “Output regulation for linear discrete-time systems subject to input saturation,” Int. J. of Robust and Nonlinear Control, Vol.1, pp. 1003-1021, 1997. https://doi.org/10.1002/(SICI)1099-1239(199711)7:11<1003::AID-RNC252>3.0.CO;2-2
- [22] D. Limon, I. Alvarado, and E. F. Casmacho, “MPC for tracking of piece-wise constant references for constrained linear systems,” IFAC Proc. Volumes, Vol.38, Issue 1, pp. 135-140, 2005. https://doi.org/10.3182/20050703-6-CZ-1902.00883
- [23] J. Kautsky and N. K. Nichols, “Robust pole assignment in linear state feedback,” Int. J. of Control, Vol.41, Issue 5, pp. 1129-1155, 1985. https://doi.org/10.1080/0020718508961188
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.