Two-degree-of-freedom MIMO control for hydraulic servo-systems with switching properties

Schröders, Simon; Maier, Clemens C.; Ebner, Wolfgang; Fidlin, Alexander; Hametner, Christoph

doi:10.1016/j.conengprac.2019.104246

Cited by 6 publications

(1 citation statement)

References 19 publications

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“…Since the above error phenomena are mostly caused by a series of nonlinear factors considered in the design of a servo system, it is obvious that the pure linear theory cannot give a reasonable or reliable explanation for the system. Generally speaking, the static parameters, stiffness, and action response of hydraulic servo system control are directly related to the functional stability of the control system, especially the nonlinearity of the valves in the electro-hydraulic servo system, which has certain limitations on the system [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Clearance Nonlinear Control Method of Electro-Hydraulic Servo System Based on Hopfield Neural Network

Wang,

Song

2024

Machines

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The electro-hydraulic servo system has advantages such as high pressure, large flow, and high power, etc., which can also realize stepless regulation, so it is widely used in many engineering machineries. A linear model is sometimes only a simple approximation of an idealized model, but in an actual system, there may be nonlinear and transient variation characteristics in the systems. Coupling is reflected in the fact that the components or functional structures implemented by each system used for the design of hydraulic systems are not completely or independently related to each other, but affect each other. The nonlinear clearance between the actuator and the load reduces the control accuracy of the system and increases the impact, thus losing stable working conditions. In the paper, based on the nonlinear clearance problem of the electro-hydraulic servo system, a mathematical transfer model with clearance is established, and on this basis, a clearance compensation method based on the Hopfield neural network is proposed. In this way, clearance compensation can be realized by adjusting the parameters of neural network nodes, through simple and convenient operation. Finally, by setting different clearance values, the results of the step response and sine response curve before and after clearance compensation of the hydraulic system are compared, and the effectiveness of Hopfield neural network compensation clearance control is verified based on the comparison simulation results.

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Section: Introductionmentioning

confidence: 99%