天钩
模型预测控制
簧载质量
控制理论(社会学)
控制器(灌溉)
加速度
执行机构
悬挂(拓扑)
主动悬架
工程类
还原(数学)
航程(航空)
计算机科学
控制工程
控制(管理)
阻尼器
数学
同伦
生物
农学
纯数学
经典力学
人工智能
航空航天工程
几何学
物理
电气工程
作者
Johan Theunissen,Aldo Sorniotti,Patrick Gruber,Saber Fallah,Marco Ricco,Michal Kvasnica,Miguel Dhaens
标识
DOI:10.1109/tie.2019.2926056
摘要
Latest advances in road profile sensors make the implementation of preemptive suspension control a viable option for production vehicles. From the control side, model predictive control (MPC) in combination with preview is a powerful solution for this application. However, the significant computational load associated with conventional implicit model predictive controllers is one of the limiting factors to the widespread industrial adoption of MPC. As an alternative, this article proposes an explicit model predictive controller (e-MPC) for an active suspension system with preview. The MPC optimization is run offline, and the online controller is reduced to a function evaluation. To overcome the increased memory requirements, the controller uses the recently developed regionless e-MPC approach. The controller is assessed through simulations and experiments on a sport utility vehicle demonstrator with controllable hydraulic suspension actuators. For frequencies <; 4 Hz, the experimental results with the regionless e-MPC without preview show a ~10% reduction of the root-mean-square (RMS) value of the vertical acceleration of the sprung mass with respect to the same vehicle with a skyhook controller. In the same frequency range, the addition of preview improves the heave and pitch acceleration performance by a further 8 to 21%.
科研通智能强力驱动
Strongly Powered by AbleSci AI