• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1459-1464
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• 1996

The most important parameter for hydraulic active suspension system is to sustain desirable vehicle maneuvering stability and ride comfort without increasing consumption power. The performance of hydraulic active suspension system depends on damping force of body damping valve and piston damping valve. Hydraulic actuator design and damping valve parameter selection are essential and basic procedure to design hydraulic active suspension system. This paper is on computer simulation with use of mathematical model that was delivered from dynamic characteristic of hydraulic actuator, as know basic damping characteristics of hydraulic active suspension system. The aim of this paper is to select the system parameter that affect mainly hydraulic active suspension, and identify the validity on the system parameter selection.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.4
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• pp.683-692
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• 2002

The most important parameter for hydraulic active suspension system is to sustain desirable vehicle maneuvering stability and ride comfort without increasing power consumption. The performance of hydraulic active suspension system depends on damping force of body damping valve and piston damping valve. Hydraulic actuator design and damping valve parameter selection are essential and basic procedure to design hydraulic system. This paper is on computer simulation with use of mathematical model that was delivered from dynamic characteristic of hydraulic actuator, as know basic damping characteristics of hydraulic active suspension system. The aim of this paper is to select the system parameter that affect mainly hydraulic active suspension, and identify the validity on the system parameter selection.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.1
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• pp.136-144
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• 2004

In general a hydraulic system which uses a single rod hydraulic as an actuator is modeled as a nonlinear system and reveals uncertain Parameter characteristics such as the density variation of hydraulic oil and is subject to load variations and severe disturbances during operation. A variable design-parameter fuzzy PID controller is adopted to solve these undesirable internal and external problems and its effectiveness is verified through computer simulations for control performance and real time control possibility.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.957-961
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• 1991

The parameters of electro-hydraulic servo system are closely dependent on the variation of system characteristics. Especially the parameter sensitivity is incleased in the servo system with heavy load and wide operating range. This paper shows the effect of parameter variation and the experimental parameter values of high power servo system.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.192-199
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• 2002

This paper demonstrates that hybrid neural-genetic multimodel parameter estimation algorithm can be applied to structured system Identification of electro-hydraulic servo system. This algorithm are consist of a recurrent incremental credit assignment (ICRA) neural network and a genetic algorithm. The ICRA neural network evaluates each member of a generation of model and genetic algorithm produces new generation of model. We manufactured electro-hydraulic servo system and the hybrid neural-genetic multimodel parameter estimation algorithm is applied to the task to find the parameter values(mass, damping coefficient, bulk modulus, spring coefficient) which minimize total square error.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.6
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• pp.442-447
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• 2003

This paper demonstrates that a modified hybrid neural-genetic multimodel parameter estimation algorithm can be applied to structured system identification of an electro-hydraulic servo system. This algorithm is consists of a recurrent incremental credit assignment(ICRA) neural network and a genetic algorithm. The ICRA neural network evaluates each member of a generation of model and genetic algorithm produces new generation of model. The modified hybrid neural-genetic multimodel parameter estimation algorithm is applied to an electro-hydraulic servo system the task to find the parameter values such as mass, damping coefficient, bulk modulus, spring coefficient and disturbance, which minimizes the total square error.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.5
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• pp.196-203
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• 2003

This paper demonstrates that an improved hybrid neural-genetic multimodel parameter estimation algorithm can be applied to the structured system identification of an electro-hydraulic servo system. This algorithm is consists of a recurrent incremental credit assignment (ICRA) neural network and a genetic algorithm, The ICRA neural network evaluates each member of a generation of model and the genetic algorithm produces new generation of model. We manufactured an electro-hydraulic servo system and the improved hybrid neural-genetic multimodel parameter estimation algorithm is applied to the task to find the parameter values, such as mass, damping coefficient, bulk modulus, spring coefficient and disturbance, which minimize total square error.

• Journal of Drive and Control
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• v.15 no.4
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• pp.67-73
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• 2018

The paper deals with an approach to time domain simulation for closed end at the downstream of pipe, hydraulic lines terminating into a tank and series lines with change of cross sectional area. Time domain simulation of a fluid power systems containing hydraulic lines is very complex and difficult if the transfer functions consist of hyperbolic Bessel functions which is the case for the distributed parameter dissipative model. In this paper, the magnitudes and phases of the complex transfer functions of hydraulic lines are calculated, and the MATLAB Toolbox is used to formulate a rational polynomial approximation for these transfer functions in the frequency domain. The approximated transfer functions are accurate over a designated frequency range, and used to analyze the time domain response. This approach is usefully to simulate fluid power systems with hydraulic lines without to approximate the frequency dependent viscous friction.

• Transactions of The Korea Fluid Power Systems Society
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• v.5 no.2
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• pp.20-26
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• 2008

The most vehicle active suspension system is activated by a hydraulic source and transmission system which has nonlinear characteristics. Even though we have designed a proper controller for this system, it sometimes cannot show remarkable performance characteristics because of many factors that undercut the performance of the hydraulic system, such as nonlinearity, modelling errors, parameter variations etc. So, the robust controller that prevents a system from lowering its performance is needed. In this study, the sliding mode control which is the representative one of robust controllers is adopted to investigate system parameter sensibility. As a result, the sliding mode controller shows robustness to the system parameters variations relative to the other controllers.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.6
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• pp.347-353
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• 2019

Electric-hydraulic sever cylinders are used in many offshore applications such as wind energy farms, solar farms and plants. Jack-up barges are often used for these offshore system operations. Jack-up barge control is up/down by hydraulic cylinder position control. Working in harsh environments can lead to changes in internal parameters. This nonlinearity makes precise control difficult. In order to overcome the problems, we proposed a method of unknown-parameter estimation algorithm based on measurements obtained by system. In this paper, we employee Unscented Kalman filter (UKF) to estimate states and unknown-parameter from augmented nonlinear equation. Performance of estimation results is verified in simulation on an environments of Matlab. The estimation results of the state and unknown-parameter show that the estimation error of unknown-parameter is reduced according to decreasing the state estimation error.