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首页> 外文期刊>International Journal of Modelling, Identification and Control >Robust Controller Design For Active Suspensions Using Particle Swarm Optimisation
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Robust Controller Design For Active Suspensions Using Particle Swarm Optimisation

机译:基于粒子群算法的主动悬架鲁棒控制器设计

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The paper presents a design technique for a fixed-structure PD robust controller of car active suspension systems. The design takes into consideration the uncertainty of system parameters, particularly tyre stiffness and body mass. Robustness is achieved by tuning the controller over a set of operating conditions covering the whole range of system parameters, e.g., body mass and tyre stiffness. Particle swarm optimisation (PSO) is used to attain different performance objectives of the system. Settling time of body displacement is minimised, system damping is maximised, and actuator saturation is avoided via control effort reduction. The design of controller parameters is cast in a multi-objective non-linear optimisation problem, and described to ensure the best possible performance. Simulation results show the superiority of the proposed system relative to the classical passive suspension, and signify robustness of the active controller design.
机译:本文提出了一种用于汽车主动悬架系统的固定结构PD鲁棒控制器的设计技术。该设计考虑了系统参数的不确定性,尤其是轮胎刚度和车身质量。通过在覆盖整个系统参数范围(例如体重和轮胎刚度)的一组运行条件下调节控制器,可以实现鲁棒性。粒子群优化(PSO)用于实现系统的不同性能目标。车身位移的建立时间最小化,系统阻尼最大化,并且通过减少控制工作量避免了执行器饱和。控制器参数的设计存在于多目标非线性优化问题中,并进行了描述,以确保获得最佳的性能。仿真结果表明了该系统相对于经典的被动悬架系统的优越性,并表明了主动控制器设计的鲁棒性。

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