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Parameter identification and robust vibration control of a truck driver’s seat system using multi-objective optimization and genetic algorithm
Applied Acoustics ( IF 3.4 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.apacoust.2020.107697
Yuli Zhao , Mohammed Alashmori , Fengrong Bi , Xu Wang

Abstract This paper has developed a 5-DOF driver and seat suspension system model for active vibration control. A novel fast system parameter identification method from vibration measurement data has been proposed for the seat-occupant system based on the multi-objective Genetic Algorithm optimization (GA). This system parameter identification method can identify the seat system parameters of a 5-DOF lumped mass-spring-dashpot biodynamic seat-occupant model from vibration test results quickly and accurately. Without calculation and measurement of materials, the physical parameters of the seat suspension system such as masses (m), stiffness (k), and damping coefficients (c) are estimated through matching the measured resonant frequency and transmissibility amplitude at a specific frequency with the simulated ones. This is one of the main contributions of this paper. The characteristics of the human body vibration in the low-frequency range are analyzed through the seat to head transmissibility (STHT) ratio. The experimental and simulation results of the STHT values have been calculated and compared to verify each other. The sensitivity analysis of the seat effective amplitude transmissibility (SEAT) values over the seat system parameters have been conducted and validated by the measured results of the transmissibility ratios. A full state feedback controller has been developed to reduce the human body vibration in the seat suspension system, which is another new contribution of this paper. The simulation results show that the proposed controller has better vibration attenuation performance than the conventional PID controller.

中文翻译:

基于多目标优化和遗传算法的货车驾驶员座椅系统参数辨识与鲁棒振动控制

摘要 本文开发了一种用于主动振动控制的五自由度驾驶员和座椅悬架系统模型。提出了一种基于多目标遗传算法优化(GA)的座椅乘员系统振动测量数据快速系统参数识别方法。该系统参数辨识方法可以快速准确地从振动测试结果中辨识出5自由度集总质量-弹簧-缓冲器生物动力座椅-乘员模型的座椅系统参数。无需对材料进行计算和测量,座椅悬挂系统的质量(m)、刚度(k)和阻尼系数(c)等物理参数通过将测量的共振频率和特定频率下的传输幅度与模拟的。这是本文的主要贡献之一。通过座头传递率(STHT)比分析低频范围内人体振动的特性。对STHT值的实验和仿真结果进行了计算和比较以相互验证。座椅有效振幅传递率 (SEAT) 值对座椅系统参数的敏感性分析已经通过传递率比的测量结果进行并验证。开发了一种全状态反馈控制器来减少座椅悬挂系统中的人体振动,这是本文的另一个新贡献。仿真结果表明,所提出的控制器比传统的PID控制器具有更好的减振性能。通过座头传递率(STHT)比分析低频范围内人体振动的特性。对STHT值的实验和仿真结果进行了计算和比较以相互验证。座椅有效振幅传递率 (SEAT) 值对座椅系统参数的敏感性分析已经通过传递率比的测量结果进行并验证。开发了一种全状态反馈控制器来减少座椅悬挂系统中的人体振动,这是本文的另一个新贡献。仿真结果表明,所提出的控制器比传统的PID控制器具有更好的减振性能。通过座头传递率(STHT)比分析低频范围内人体振动的特性。对STHT值的实验和仿真结果进行了计算和比较以相互验证。座椅有效振幅传递率 (SEAT) 值对座椅系统参数的敏感性分析已经通过传递率比的测量结果进行并验证。开发了一种全状态反馈控制器来减少座椅悬挂系统中的人体振动,这是本文的另一个新贡献。仿真结果表明,所提出的控制器比传统的PID控制器具有更好的减振性能。
更新日期:2021-02-01
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