Application of adaptive robust control for electro-hydraulic motion loading system

Abstract

This paper investigates the problem of the high-performance motion loading control of an electro-hydraulic load simulator (EHLS). To begin with, the non-linear motion loading model of the EHLS was developed, by which the external disturbances caused by actuator active motion and the uncertainties arising from the EHLS were comprehensively considered. To address these uncertainties and disturbances, the adaptive robust torque control algorithm was developed with the motion loading model. In contrast to the available control methods concerning the EHLS, the developed method has two advantages. First, instead of performing the fixed coefficients-based linear feed-forward compensation using the actuator velocity, adaptive non-linear feed-forward compensation is achieved through the back-stepping design procedure. Second, the uncertainties and disturbances including system parametric uncertainties, un-modelled friction dynamics and unknown external disturbance are addressed comprehensively. Besides illustrating the theoretical proof, the effectiveness of the proposed method is verified through comparative experiments.

Parameter adaptive based neural network sliding mode control for electro‐hydraulic system with application to rock drilling jumbo

“…Achieving high quality control of hydraulic systems under the influence of numerous uncertainties has been a hot research topic in both academia and industry 10 . To cope with the parameters uncertainties and unmodeled dynamics of hydraulic systems, the popular control algorithms can be broadly classified into four categories, the first is observer‐based control, 11–15 the second is neural network or fuzzy control, 16–19 the third is parameter adaptive‐based control, 20–27 the fourth is the combination of these methods 28,29 …”

“…Achieving high quality control of hydraulic systems under the influence of numerous uncertainties has been a hot research topic in both academia and industry. 10 To cope with the parameters uncertainties and unmodeled dynamics of hydraulic systems, the popular control algorithms can be broadly classified into four categories, the first is observer-based control, [11][12][13][14][15] the second is neural network or fuzzy control, [16][17][18][19] the third is parameter adaptive-based control, [20][21][22][23][24][25][26][27] the fourth is the combination of these methods. 28,29 In general, observer-based control algorithms regard parameters uncertainties and external disturbances as the "total disturbance," 12,13,15 the advantages are that the algorithm is simple and can be implemented easily, but the shortcoming is not detailed enough in dealing with parameters uncertainties, and it may add additional burden to the observer if system has large parameters uncertainties.…”

Nonlinear position control of electro-hydraulic servo system based on lyapunov robust integral backstepping controller

“…The utilization of Electrohydraulic Servo Systems (EHSS) is prevalent in numerous industrial applications and advanced automation systems owing to their exceptional attributes, including positioning capabilities, a highpower ratio, fast and effortless response, rigidity, and the ability to generate substantial force [1]. The application of EHSS has been observed in diverse mechanical systems, including hydraulic robot manipulators, hydraulic presses, load simulators, and active suspension systems for vehicles, and has had a substantial impact on modern position control devices due to its effective positioning capability [2][3][4][5][6][7][8][9][10][11]. However, to achieve accurate positioning in the said applications, a dependable electro-hydraulic actuator is deemed necessary.…”

Optimal robust adaptive fuzzy backstepping control of electro-hydraulic servo position system

“…Recently, in control of highly nonlinear systems that have the parametric uncertainties, adaptive control techniques have been used where they have played a crucial role (Chengwen et al, 2018). In the EHS system position control, adaptive control has also been used (Sadeghieh et al, 2012;Yin et al, 2019).…”