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Vibration control of an active vehicle suspension systems using optimized model-free fuzzy logic controller based on time delay estimation

机译:基于时延估计的优化无模型模糊逻辑控制器的主动车辆悬架系统振动控制

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This paper presents a new model-free fuzzy logic controller based on particle swarm optimization (PSO-MFFLC) for the nonlinear active suspension systems. The proposed method comprises the model-free based intelligent PID controller, the fuzzy logic controller, the time-delay estimation, and the particle swarm optimization. The advantage of PSO-MFFLC is quite simple structure and easy to be regulated. To validate the proposed controller, the nonlinear active suspension systems with non-linearity such as the parameters variation, external disturbance, and friction force effect are simultaneously taking into account to provide a realistic framework. The control objective is to deal with the classical conflict between minimizing vertical chassis acceleration to increase the ride comfort and keeping the dynamic wheel load small in order to ensure the ride safety. Moreover, modeling performed using a virtual detailed simulation environment LMS-AMESim, while the control part configured on Matlab/Simulink. Finally, the comparison of PSO-MFFLC with a classical PID, intelligent PID and the time-delay estimation control (TDEC) is conducted for different roads disturbances.
机译:针对非线性主动悬架系统,本文提出了一种基于粒子群算法的新型无模型模糊逻辑控制器(PSO-MFFLC)。该方法包括基于无模型的智能PID控制器,模糊逻辑控制器,时延估计和粒子群算法。 PSO-MFFLC的优点是结构非常简单且易于调节。为了验证所提出的控制器,同时考虑了具有非线性(例如参数变化,外部干扰和摩擦力效应)的非线性主动悬架系统,以提供一个现实的框架。控制目标是应对经典冲突,即最大程度地减小垂直底盘加速度以增加行驶舒适性,并保持较小的动态车轮载荷以确保行驶安全。此外,在控制部分配置在Matlab / Simulink上的同时,使用虚拟详细仿真环境LMS-AMESim进行了建模。最后,针对不同的道路干扰情况,将PSO-MFFLC与经典PID,智能PID和时延估计控制(TDEC)进行了比较。

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