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Model predictive control of dynamically substructured systems with application to a servohydraulically actuated mechanical plant

机译:动态子结构系统的模型预测控制及其在伺服液压致动机械装置中的应用

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摘要

Dynamically substructured systems (DSS) are increasingly used by the dynamics testing community. DSS involves the physical testing of full-size critical components in parallel with numerical testing of the remaining components. This has certain advantages over other testing methods. However, the synchronisation of the signals at the interface between the physical and numerical substructures of DSS requires a high fidelity controller. In practice, the performance of the DSS testing can be degraded by input saturation of the actuators. In this study, the authors use model predictive control (MPC) to cope with the saturation problem in DSS. To facilitate the MPC and observer design for DSS, a modified DSS framework based on an existing one is proposed. As a case study, a quasi-motorcycle (QM) system is converted into the modified DSS framework and a traditional on-line MPC control strategy is implemented in real time.
机译:动态测试系统越来越多地使用动态子结构化系统(DSS)。 DSS涉及对全尺寸关键组件的物理测试,以及对其余组件的数值测试。与其他测试方法相比,这具有某些优势。但是,DSS的物理子结构和数字子结构之间的接口处的信号同步需要高保真度的控制器。实际上,执行器的输入饱和会降低DSS测试的性能。在这项研究中,作者使用模型预测控制(MPC)来解决DSS中的饱和度问题。为了方便MPC和DSS的观察者设计,提出了一种基于现有框架的改进的DSS框架。作为案例研究,将准摩托车(QM)系统转换为改进的DSS框架,并实时实施传统的在线MPC控制策略。

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