Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models

Muthalif, Asan G. A.; Razali, M. Khusyaie M.; Nordin, N. H. Diyana; Hamid, Syamsul Bahrin Abdul

doi:10.1109/access.2021.3080432

Cited by 14 publications

(3 citation statements)

References 44 publications

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“…From the perspective of product content, leisure snacks in Figure 11 refer to a kind of ready-to-eat food that complements the hunger demand outside the dinner. Leisure food emphasizes the extended value of consumption scenario, meeting more emotions and functions [17]. According to the statistical data analysis, as shown in Figure 12, the annual output value of China's leisure food industry increased from 401.4 billion yuan in 2010 to 919.1 billion yuan in 2017, with an average annual compound growth rate of 12.56%, and it is expected to maintain high growth from 2018 to 2020, from 1029.7 billion yuan in 2018 to 1298.4 billion yuan in 2020, with an average annual compound growth rate of 12.29%.…”

Section: Stp Analysismentioning

confidence: 99%

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

Xue

2022

Mobile Information Systems

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In order to deeply study the macroenvironment, current situation, and the core elements affecting the operation of the product brand system, this paper further improves the product brand communication system from the perspective of precision marketing. Taking JR company’s big cake products as the research object, this study proposes an accurate positioning optimization algorithm based on particle swarm optimization algorithm. Through the experiment of increasing the number of nodes of different algorithms, it is found that the average positioning error will decrease with the increase of the number of nodes under different algorithms. Compared with WSSPCO positioning algorithm, the average error of PSO positioning algorithm is reduced by about 30% due to the number of nodes, and the impact of node density on positioning accuracy is also reduced by about 40%. This algorithm can better achieve accurate positioning. Therefore, it is concluded that product brand communication based on precision marketing should pay attention to accurate positioning, further integrate brand communication channels, and build personalized communication channels.

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Section: Stp Analysismentioning

confidence: 99%

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

Xue

2022

Mobile Information Systems

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“…There are mainly two kinds of strategies to control the MRDs: One is to directly use the input current as the controller output target value [10,11]. The other is to use the damping force as the design basis of the controller, and it is necessary to establish an inverse model of the damping and the input current [12,13].…”

Section: Introductionmentioning

confidence: 99%

A forward-inverse dynamic model for the hydraulic damping(magnetorheological) actuator based on cyclic stress–strain

Ma,

Huang,

Huang

et al. 2024

Smart Mater. Struct.

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Magnetorheological dampers (MRDs) are applied to hydraulic systems, which not only improve the underdamped characteristics of valve-controlled cylinder systems, but also help hydraulic actuators to resist high load impact. However, the high power density leads to the complexity of the internal flow channel of the damper, which seriously affects the output accuracy of the damping force. It can lead to the fact that existing dynamics models cannot accurately describe the hysteresis characteristics of the MRD. Therefore, this study proposes a simple and general dynamic model of MRD, which solves the problem that existing models are complex and difficult to invert. Firstly, the hydraulic damping actuator (HDA) with the series MRD is taken as the research object. Based on the stress-strain hysteresis characteristics under the cyclic constitutive model, the hyperbolic tangent curve is reorganized and normalized. It can accurately describe the yield formation and yield dissipation stages of the hysteresis loop. Secondly, the relationship between the parameters of the dynamic model and the current is obtained according to the mechanical experimental data. Then the inverse model of the MRD is established by using the method of section-backstepping. Finally, in the static experiment, the Mean Absolute Percentage Error(MAPE) of the force at different velocity is less than 7.5%; In the dynamic experimental test, the MAPE of the force is 9.7%. The inverse dynamics model is verified to have high tracking performance under both static and dynamic forces. And it also indirectly confirms the effectiveness of the forward model.

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“…33,34 PSO offers several advantages: it performs well in high-dimensional problems, provides uniform sampling of the search space, and results in quicker convergence, shorter computation times, and resource savings. 35,36 Consequently, this study selects PSO to optimize fuzzy PID controller parameters due to its computational efficiency and convergence performance.…”

Section: Introductionmentioning

confidence: 99%

Particle swarm optimized fuzzy proportional-integral-derivative controller-based transverse leaf spring active suspension for vibration control

Zhang,

Long,

Lin

et al. 2023

Journal of Low Frequency Noise, Vibration and Active Control

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The transverse leaf spring (TLS) suspensions are a promising option for van vehicles due to their high load-carrying capacity and excellent handling stability. However, its ride comfort remains a major challenge. This paper investigates and compares the effects of semi-active and active control strategies to enhance the ride comfort of TLS suspensions. Firstly, a four-degree-of-freedom (4-DOF) half-car model and a multi-body dynamics (MBD) model of the TLS suspensions are established. The MBD model has higher accuracy and can describe the medium and high frequency characteristics of the TLS suspensions, such as the suspension offset frequency and the frequency response function of the body vertical acceleration (BVA). Therefore, based on the MBD half-car model with TLS suspensions, this paper proposes an optimal fuzzy PID active control strategy considering the left and right suspension coupling. The optimization objectives are the BVA, the left and right suspensions dynamic deflection, and the left and right wheels dynamic displacement. The integral absolute error is used as the evaluation criterion. The left and right fuzzy PID controllers’ parameters are obtained through particle swarm optimization. Simulation results demonstrate that the particle swarm optimization fuzzy PID active control strategy effectively controls the low-frequency vibration of the TLS suspensions and suppresses the medium- and high-frequency vibration characteristics compared with the traditional skyhook semi-active control strategy. This technology provides a reference for improving the ride comfort of the TLS suspensions.

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Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models

Cited by 14 publications

References 44 publications

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

A forward-inverse dynamic model for the hydraulic damping(magnetorheological) actuator based on cyclic stress–strain

Particle swarm optimized fuzzy proportional-integral-derivative controller-based transverse leaf spring active suspension for vibration control

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