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Optimized Proportional Integral Derivative Controller of Vehicle Active Suspension System Using Genetic Algorithm

机译:基于遗传算法的车辆主动悬架系统优化的比例整体衍生控制器

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Proportional integral derivative (PID) control method is an effective, easy in implementation and famous control technique applied in several engineering systems. Also, Genetic Algorithm (GA) is a suitable approach for optimum searching problems in science, industrial and engineering applications. This paper presents the usage of GA for determining the optimal PID controller gains and their implementation in the active quarter-vehicle suspension system to achieve good ride comfort and vehicle stability levels. The GA is applied to solve a combined multi-objective (CMO) problem to tune PID controller gains of vehicle active suspension system for the first time. The active vehicle suspension system is modeled mathematically as a two degree-of-freedom mechanical system and simulated using Matlab/Simulink software. The performance of the proposed suspension system controlled using the optimized PID GA is compared to both controlled system using the classical PID (C PID) controller and the passive suspension systems. Systems performance criteria are evaluated in both time and frequency domains, in order to quantify the success of the proposed suspension system. The theoretical results reveal that the proposed optimized PID GA controller of the active vehicle suspension provides a vital enhancement of ride comfort and vehicle stability levels.
机译:比例整体衍生物(PID)控制方法是在若干工程系统中应用的有效,易于实现和着名的控制技术。此外,遗传算法(GA)是一种适用于科学,工业和工程应用中的最佳搜索问题的合适方法。本文介绍了GA用于确定最佳PID控制器收益及其在活动季度车辆悬架系统中的实现,以实现良好的乘坐舒适度和载体稳定性水平。遗址应用于解决组合的多目标(CMO)问题,首次调谐车辆主动悬架系统的PID控制器。主动车辆悬架系统以两自由度的机械系统在数学上进行建模,并使用MATLAB / SIMULINK软件进行模拟。使用经典PID(C PID)控制器和无源悬架系统,将使用优化PID GA控制的所提出的悬架系统的性能进行比较。系统性能标准在两个时间和频率域中进行评估,以量化所提出的悬架系统的成功。理论结果表明,主动车辆悬架的所提出的优化PID GA控制器提供了乘坐舒适度和车辆稳定性水平的重要增强。

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