Abstract:Dynamic simulation of mechanical systems can be performed using a multibody system dynamics approach. The approach allows to account systems of other physical nature, such as hydraulic actuators. In such systems, the nonlinearity and numerical stiffness introduced by the friction model of the hydraulic cylinders can be an important aspect to consider in the modeling because it can lead to poor computational efficiency. This paper couples various friction models of a hydraulic cylinder with the equations of mot… Show more
“…In Figures 12,13, and 14, all outputs of the NVLCC show better dynamic performance compared with the PID controller. Notably, significant phase lag and waveform distortion are remarkably improved when c ¼ 0:1.…”
Section: Simulations and Analysismentioning
confidence: 99%
“…The internal factors are the inherent characteristics of the electrohydraulic system that the regulation of which will not change for a very long time until some parts of the system are failed, including dead zone, hysteresis, friction, and so forth. [11][12][13] Therefore, the models of these internal factors can be obtained by repetitive experiments or some analyzing algorithms. That means a model-based controller can be easily designed to compensate the effect that whatever internal factors bring into the system.…”
In an electrohydraulic system, the load is an external factor that cannot obtain similar results by repetitive experiments compared with other internal factors. It can work a great change in an extremely short time determined by the characteristics of the loaded object, which is more difficult to be identified timely and compensated precisely. This paper first built the mathematic model of the electrohydraulic system containing load characteristics and illustrated most kinds of basic loads that possibly occur in it. Then, a practice nonlinear variable load composed of these basic loads is presented, and the corresponding effect to the electrohydraulic system is analyzed. Based on the summary of load, a nonlinear variable load compensation controller (NVLCC) with neural networks is proposed to identify the mathematic model of the electrohydraulic system. The nonlinear variable load is considered as a part of the model to be globally identified, and an adaptive sliding mode control method is combined to quickly converge the errors of system state variables. The compensation effectiveness is demonstrated by both rigid step response and dynamic sine response in the simulations, and the actual improvements are verified with the experiments using three different typical linear loaded objects and a representative nonlinear loaded object.
“…In Figures 12,13, and 14, all outputs of the NVLCC show better dynamic performance compared with the PID controller. Notably, significant phase lag and waveform distortion are remarkably improved when c ¼ 0:1.…”
Section: Simulations and Analysismentioning
confidence: 99%
“…The internal factors are the inherent characteristics of the electrohydraulic system that the regulation of which will not change for a very long time until some parts of the system are failed, including dead zone, hysteresis, friction, and so forth. [11][12][13] Therefore, the models of these internal factors can be obtained by repetitive experiments or some analyzing algorithms. That means a model-based controller can be easily designed to compensate the effect that whatever internal factors bring into the system.…”
In an electrohydraulic system, the load is an external factor that cannot obtain similar results by repetitive experiments compared with other internal factors. It can work a great change in an extremely short time determined by the characteristics of the loaded object, which is more difficult to be identified timely and compensated precisely. This paper first built the mathematic model of the electrohydraulic system containing load characteristics and illustrated most kinds of basic loads that possibly occur in it. Then, a practice nonlinear variable load composed of these basic loads is presented, and the corresponding effect to the electrohydraulic system is analyzed. Based on the summary of load, a nonlinear variable load compensation controller (NVLCC) with neural networks is proposed to identify the mathematic model of the electrohydraulic system. The nonlinear variable load is considered as a part of the model to be globally identified, and an adaptive sliding mode control method is combined to quickly converge the errors of system state variables. The compensation effectiveness is demonstrated by both rigid step response and dynamic sine response in the simulations, and the actual improvements are verified with the experiments using three different typical linear loaded objects and a representative nonlinear loaded object.
“…The force produced by the cylinder can be expressed as: where and are, respectively, the pressures on the piston and piston-rod sides, and is the total friction force [ 5 ] caused by the seal. The friction force from sealing can be computed using various friction models as presented by the authors in [ 18 ]. In this study, a continuous static friction model, namely, Brown-McPhee friction model [ 5 ], is utilized because it can describe the usual friction characteristics with a computationally efficient approach, as presented by the authors in [ 18 ].…”
Section: Multibody Formulationmentioning
confidence: 99%
“…The friction force from sealing can be computed using various friction models as presented by the authors in [ 18 ]. In this study, a continuous static friction model, namely, Brown-McPhee friction model [ 5 ], is utilized because it can describe the usual friction characteristics with a computationally efficient approach, as presented by the authors in [ 18 ]. Fig.…”
In multibody system dynamics, the equations of motion are often coupled with systems of other physical nature, such as hydraulics. To infer the real dynamical state of such a coupled multibody system at any instant of time, information fusing techniques, such as state estimators, can be followed. In this procedure, data is combined from the coupled multibody model and the physical sensors installed on the actual machine. This paper proposes a novel state estimator developed by combining a multibody model with an indirect Kalman filter in the framework of hydraulically driven systems. An indirect Kalman filter that utilizes the exact Jacobian matrix of the plant at position and velocity level is extended for hydraulically actuated systems. The structures of the covariance matrices of the plant and measurement noise are also studied. The multibody system, described using a semi-recursive formulation, and the hydraulic subsystem, described using lumped fluid theory, are coupled using a monolithic approach. As a case study, the state estimator is applied to a hydraulically actuated four-bar mechanism. The state estimator considers modeling errors in the force model because of its uncertainty in modeling. The measurements are obtained from a dynamic model which is considered as the ground truth, with an addition of white Gaussian noise to represent the noise properties of the actual sensors. The state estimator uses four sensor configurations with different sampling rates. For the presented case study, the state estimator can accurately estimate the work cycle and hydraulic pressures of the coupled multibody system. The results demonstrate the efficacy of the proposed state estimator.
“…The external load appears in the SF and PM phases of the pressing cycle. The values of slider friction parameters shown in Table 6 are achieved by the literature review and modified from the prototype model [28,29]. The model of the hydraulic cylinder is built based on the compressibility of the fluid in the cylinder chambers, leakage, damping coefficient on end stops and deformation on end stops at which the damping rate is fully effective.…”
This paper will develop a novel electro-hydraulic actuator with energy saving characteristics. This system is able to work in differential configurations through the shifting algorithm of the valves, meaning that this developed system can be adjusted flexibly to obtain the desirable working requirements including the high effectiveness of energy recovery from the load, high velocity or torque. Instead of establishing the mathematical model for the purpose of the dynamic analysis, a model of the developed actuator is built in AMESim software. The simulation results reveal that the system is able to save approximately 20% energy consumption compared with a traditional without energy recovery EHA. Furthermore, to evaluate the accuracy of the model, experiments will be performed that prove strongly that the experimental results are well matched to the results attained from the simulation model. This work also offers a useful insight into designing and analyzing hydraulic systems without experiments.
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