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Fuzzy logic with a novel advanced firefly algorithm and sensitivity analysis for semi-active suspension system using magneto-rheological damper

机译:具有磁流变阻尼器的新型主动萤火虫算法的模糊逻辑和半主动悬架系统的灵敏度分析

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Semi-active suspension control with magnetorheological (MR) damper is one of the fascinating systems being studied in improving the vehicle dynamics. By using the MR damper system, a controllable system can be produced dynamically and the majority of the performance of a fully active system can potentially be achieved. Since the conventional optimization method always has a problem in identifying the optimum values and it is time consuming, the evolutionary algorithm is the best approach in replacing the conventional method as it is very efficient and consistent in exploring the values for every single space. In this study, the semi-active control schemes, namely fuzzy logic based controllers tuned using a novel optimization algorithm called advanced firefly algorithm (AFA) is proposed to regulate the body of the vehicle's suspension from any disturbances acted to the system. The AFA is to be introduced based on the improvement of the original firefly algorithm (FA) to enhance the solution quality of the FA. The comparative assessment study of the proposed optimizer with other evolutionary algorithm, called the particle swarm optimization (PSO) is also presented. A simulation of semi-active suspension system with two degree of freedom is developed within MATLAB Simulink environment. The simulation result indicates that the FL-AFA exhibits an improvement in terms of sprung acceleration and sprung displacement response, with 51.4% and 52.3% as compared with the FL-FA controller, FL-PSO controller, FL controller and passive systems.
机译:具有磁流变(MR)减震器的半主动悬架控制是正在研究的,旨在改善车辆动力学的引人入胜的系统之一。通过使用MR阻尼器系统,可以动态生成可控系统,并且可以潜在地实现全主动系统的大部分性能。由于常规的优化方法始终在确定最优值方面存在问题,而且很耗时,因此进化算法是替代常规方法的最佳方法,因为它在探索每个单个空间的值方面非常高效且一致。在这项研究中,提出了半主动控制方案,即基于模糊逻辑的控制器,该控制器使用一种称为高级萤火虫算法(AFA)的新型优化算法进行了调节,以调节车辆悬架的主体免受系统的任何干扰。将基于原始萤火虫算法(FA)的改进来引入AFA,以提高FA的解决方案质量。还提出了该优化器与其他进化算法(称为粒子群优化(PSO))的比较评估研究。在MATLAB Simulink环境中开发了具有两个自由度的半主动悬架系统的仿真。仿真结果表明,与FL-FA控制器,FL-PSO控制器,FL控制器和无源系统相比,FL-AFA的簧上加速度和簧上位移响应均有改善,分别为51.4%和52.3%。

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