2018
DOI: 10.1007/s11771-018-3970-x
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Dynamic friction modelling and parameter identification for electromagnetic valve actuator

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Cited by 6 publications
(7 citation statements)
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“…Finally, experimental measurements of the device displacement, velocity, and shear force were used to validate the performance of the proposed model and the IFFOA. Shao et al [56] combined chaos search and a Gaussian mutation operator into a traditional artificial fish swarm algorithm and proposed an improved artificial fish swarm algorithm (IAFSA) method. The effectiveness of the IAFSA was verified through steady-state response and dynamic friction experiments.…”
Section: Metaheuristicsmentioning
confidence: 99%
See 1 more Smart Citation
“…Finally, experimental measurements of the device displacement, velocity, and shear force were used to validate the performance of the proposed model and the IFFOA. Shao et al [56] combined chaos search and a Gaussian mutation operator into a traditional artificial fish swarm algorithm and proposed an improved artificial fish swarm algorithm (IAFSA) method. The effectiveness of the IAFSA was verified through steady-state response and dynamic friction experiments.…”
Section: Metaheuristicsmentioning
confidence: 99%
“…Artificial Fish Swarm Algorithm (AFSA) [56] The requirements for the properties of the objective function and parameter settings are low.…”
Section: Metaheuristicsmentioning
confidence: 99%
“…However, since the Coulomb’s hypothesis, a significant amount of effort has been made to establish an accurate friction model. Among them, the LuGre friction model proposed by Canudas de Wit 27 can describe both the dynamic friction and static friction with high accuracy and has been widely used in servo system and motion control; 2830 therefore, it is suitable for the conditions used in this paper. Hence, the LuGre friction model is employed to describe the friction between the mover and supporting parts of the actuator.…”
Section: Lumped Parameter Model Of the Electromagnetic Actuatormentioning
confidence: 99%
“…The recursive equations of the LuGre model were solved, and the problem of effectively detecting mane microdisplacement was discussed by Guo et al [12]. Shao proposed a new modified LuGre model suited to a high-speed mechanical system with friction as well as an improved artificial fish swarm algorithm (IAFSA) method that introduced the chaotic search and Gauss mutation operators into a traditional artificial fish swarm algorithm in order to identify the parameters in the proposed modified LuGre friction model [13]. The angular speed over the zero phenomenon occurring in the angular speed free reduction was used to acquire the microdisplacement of the mane in reference [14].…”
Section: Introductionmentioning
confidence: 99%
“…Equations 9and (13) are the mathematical descriptions of the system load and working load for the flow regulator. The next step of modeling is the identification of the model parameter.…”
mentioning
confidence: 99%