For the electro-hydraulic servo systems (EHSS) subjected to parameter uncertainties and unknown load disturbances, a model reference adaptive controller (MRAC) is proposed in this paper. Based on radial basis function neural networks (RBF NN) and nonlinear disturbance observer (NDO), it ensures a high performance in tracking output to the reference model. Firstly, a nominal MRAC is developed using Liapunov theory. In addition, a RBF NN is constructed to approximate parameter uncertainty and other nonlinear functions online. Then, the NDO is devised to estimate the nonlinear terms containing unknown load disturbances and compensate for disturbance. Besides, the stability of the closed-loop system is analyzed. Finally, the proposed controller is simulated and experimentally verified. According to the simulation results, the control method proposed in this paper is advantageous over other controllers in improving the accuracy of position tracking and enhancing the robustness of the system. Moreover, the superiority of this control method is demonstrated by the experimental results.
YangXCuiYYuanZ, et al. RISE-based adaptive control of electro-hydraulic servo system with uncertain compensation. Math Biosci Eng2023; 20(5): 9288–9304.
2.
YaoZYaoJSunW. Adaptive RISE control of hydraulic systems with multilayer neural-networks. IEEE Trans Ind Electron2019; 66(11): 8638–8647.
3.
BaghestanKRezaeiSMTalebiHA, et al. An energy-saving nonlinear position control strategy for electro-hydraulic servo systems. ISA Trans2015; 59: 268–279.
4.
ZhangJChenYXuB, et al. Effects of splined shaft bending rigidity on cylinder tilt behaviour for high-speed electro-hydrostatic actuator pumps. Chin J Aeronaut2019; 32(2): 499–512.
5.
TangJCaoJWuM, et al. Position control of electro-hydraulic servo system using active disturbance rejection control for upper-limb exoskeleton. J Vibroengineering2023; 25(3): 581–593.
6.
HuangJSongZWuJ, et al. Parameter adaptive sliding mode force control for aerospace electro-hydraulic load simulator. Aerospace2023; 10(2): 160–160.
7.
FengLYanH. Nonlinear adaptive robust control of the electro-hydraulic servo system. Appl Sci2020; 10(13): 4494.
8.
DasJMishraSKSahaR, et al. Nonlinear modeling and PID control through experimental characterization for an electrohydraulic actuation system: system characterization with validation. J Braz Soc Mech Sci Eng2017; 39(4): 1177–1187.
9.
ShenYGuoYQZhaX, et al. Real-time hybrid test control research based on improved electro-hydraulic servo displacement algorithm. Sensors (Basel)2023; 23(10): 4765.
10.
FanYShaoJSunG. Optimized PID controller based on beetle antennae search algorithm for electro-hydraulic position servo control system. Sensors2019; 19(12): 2727–2727.
11.
EnyanMBingZJunsenR, et al. Nonlinear position control of electro-hydraulic servo system based on Lyapunov robust integral backstepping controller. Eng Res Express2023; 5(4): 045024.
12.
WangYZhaoJZhangH, et al. Robust output feedback control for electro-hydraulic servo system with error constraint based on high-order sliding mode observer. Trans Inst Meas Contr2023; 45(9): 1703–1712.
13.
CaoQSuX. Generalized super-twisting backstepping sliding mode control for electro-hydraulic servo systems considering the coexistence of matched and mismatched uncertainties. Appl Sci2023; 13(8): 4931.
14.
HelianBChenZYaoB. Energy-saving and accurate motion control of a hydraulic actuator with uncertain negative loads. Chin J Aeronaut2021; 34(5): 253–264.
15.
NguyenMHDaoHVAhnKK. Adaptive robust position control of electro-hydraulic servo systems with large uncertainties and disturbances. Appl Sci2022; 12(2): 794–794.
16.
ChengwenWZongxiaJLongQ, et al. Application of adaptive robust control for electro-hydraulic motion loading system. Trans Inst Meas Contr2018; 40(3): 873–884.
17.
ZhangJLiHLiuQ, et al. The model reference adaptive impedance control for underwater manipulator compliant operation. Trans Inst Meas Contr2023; 45(11): 2135–2148.
18.
MaJZhangR. Model reference adaptive neural sliding mode control for aero-engine. AASRI Procedia2012; 3: 508–514.
19.
YaoZYaoJYaoF, et al. Model reference adaptive tracking control for hydraulic servo systems with nonlinear neural-networks. ISA Trans2020; 100: 396–404.
20.
LiuSHaoRZhaoD, et al. Adaptive dynamic surface control for active suspension with electro-hydraulic actuator parameter uncertainty and external disturbance. IEEE Access2020; 8: 156645–156653.
21.
HuangYZhangJChenD, et al. Model reference adaptive control of marine permanent magnet propulsion motor based on parameter identification. Electronics2022; 11(7): 1012–1012.
22.
ZhangYMaHXuJ, et al. Model reference adaptive vibration control of an offshore platform considering marine environment approximation. J Mar Sci Eng2023; 11(1): 138–138.
23.
HassanNSaleemA. Neural network-based adaptive controller for trajectory tracking of wheeled mobile robots. IEEE Access2022; 10: 13582–13597.
24.
JiangSWangHZhaoG. Research on neural network model reference adaptive disturbance rejection control of digital hydraulic cylinder. Adv Mech Eng2022; 14(12): 1–15.
25.
SaYZhuZTangY, et al. Adaptive dynamic surface control using nonlinear disturbance observers for position tracking of electro-hydraulic servo systems. Proc IMechE, Part I: J Systems and Control Engineering2022; 236(3): 634–653.
26.
GaoYShenGLiX, et al. Sliding-mode control of electro-hydraulic positioning tracking system combining K-observer and nonlinear disturbance observer. Proc IMechE2024; 238(2): 213–226.
27.
AljubouryASHameedAHAjelAR, et al. Robust adaptive control of knee exoskeleton-assistant system based on nonlinear disturbance observer. Actuators2022; 11(3): 78–78.
28.
WangYZhaoJDingH, et al. An energy-saving output feedback control of single-rod electrohydraulic servo system with disturbance observer. Complexity2020; 2020: 1–12.
29.
DengWYaoJMaD. Robust adaptive precision motion control of hydraulic actuators with valve dead-zone compensation. ISA Trans2017; 70: 269–278.
