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System Reconfiguration and Fault-Tolerant for Distributed Model Predictive Control Using Parameterized Network Topology

机译:使用参数化网络拓扑的分布式模型预测控制的系统重新配置和容错

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A parameterized network topology based distributed model predictive control (DMPC) framework is proposed in this work, it is mainly applied in system reconfiguration and sensor fault-tolerant control. The Lyapunov stability condition for DMPC with a parameterized network topology is derived. Regarding to system reconfiguration, the parameterized network topology is served as the explicit reconfiguration model. Furthermore, for fault-tolerant control with sensor bias, the parameterized network topology is used to compensate the sensor fault, and a residual generator is designed by states of predictor and consider a time varying threshold for fault detection. The proposed approach is able to handle the system reconfiguration and fault-tolerant control without backup controllers or controllers redesign, and there is no need of the information of fault because of the using of predictor.
机译:本文提出了一种基于参数化网络拓扑的分布式模型预测控制(DMPC)框架,该框架主要应用于系统重构和传感器容错控制。推导了具有参数化网络拓扑的DMPC的Lyapunov稳定性条件。关于系统重新配置,将参数化的网络拓扑用作显式重新配置模型。此外,对于带有传感器偏置的容错控制,可使用参数化的网络拓扑来补偿传感器故障,并通过预测器的状态设计残差生成器,并考虑时变阈值以进行故障检测。所提出的方法能够处理系统的重新配置和容错控制,而无需备用控制器或控制器的重新设计,并且由于使用了预测器,因此不需要故障信息。

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