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Whale-optimized fuzzy-fractional order controller-based automobile suspension model
Engineering Optimization ( IF 2.7 ) Pub Date : 2021-05-07 , DOI: 10.1080/0305215x.2021.1913735
P. Swethamarai 1 , P. Lakshmi 1 , S. Gokul Prassad 2
Affiliation  

The functionality of the Active Suspension System (ASS) concerning stability and ride quality offers scope in modelling and simulation of automobile active suspension model. This work explores the design and simulation of a five degree of freedom ASS based driver integrated half car model (i.e.) Active Half Car Driver (AHCD) model. A novel design approach which assesses the Fuzzy-Fractional Order PID (FFOPID) controller parameters using bio inspired Whale Optimization Algorithm (WOA) is presented. The WOA is employed to manipulate the parameters of FFOPID controller and its efficacy is investigated using a comparative study against the performance of FOPID, FFOPID and Particle Swarm Optimization (PSO) technique tuned FFOPID (PSO-FFOPID) controllers over a single bump and a random road. The ACHD model is also analyzed under different speed levels which discloses performance adaptability of the proposed WOA-FFOPID controller. The Frequency Weighted Root Mean Square and Vibration dose value as per ISO 2631-1 standards are calculated and the results thus acquired are compared comprehensively and are analyzed which confirms that the WOA-FFOPID centered AHCD model provides the best ride comfort by reducing the driver body vibration in vertical motion.



中文翻译:

基于鲸鱼优化模糊分数阶控制器的汽车悬架模型

主动悬架系统 (ASS) 有关稳定性和行驶质量的功能为汽车主动悬架模型的建模和仿真提供了空间。这项工作探讨了基于五自由度 ASS 的驾驶员集成半车模型(即主动半车驾驶员(AHCD)模型)的设计和仿真。提出了一种使用仿生鲸鱼优化算法 (WOA) 评估模糊分数阶 PID (FFOPID) 控制器参数的新颖设计方法。WOA 用于操纵 FFOPID 控制器的参数,并通过对 FOPID、FFOPID 和粒子群优化 (PSO) 技术调谐 FFOPID (PSO-FFOPID) 控制器在单个凸点和随机路。还对不同速度水平下的 ACHD 模型进行了分析,揭示了所提出的 WOA-FFFOPID 控制器的性能适应性。根据 ISO 2631-1 标准计算频率加权均方根和振动剂量值,并对所得结果进行综合比较和分析,证实以 WOA-FFOPID 为中心的 AHCD 模型通过减少驾驶员身体提供了最佳的乘坐舒适性垂直运动中的振动。

更新日期:2021-05-07
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