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Control Design of Elementary Hybrid Petri Nets via Model Predictive Control

机译:基于模型预测控制的初级混合培养皿网控制设计

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This paper addresses the control design of Hybrid Dynamic Systems (HDS) modeled by Hybrid Petri Net (HPN) systems. The resolution of the problem is based on Model Predictive Control (MPC). Our goal is to drive a HPN to reach a desired marking. Since HDS incorporates both discrete and continues processes, the proposed control strategy, called Hybrid Predictive Control, is composed of a discrete and a continuous predictive control. At each sampling period, the discrete predictive control selects a set of feasible sequences constituted of discrete immediate enabled transitions, while the continuous procedure computes the continuous constant control action over a variable prediction horizon.
机译:本文介绍了由混合Petri网(HPN)系统建模的混合动力系统(HDS)的控制设计。该问题的解决方案基于模型预测控制 (MPC)。我们的目标是推动 HPN 达到所需的标记。由于 HDS 包含离散过程和连续过程,因此所提出的控制策略称为混合预测控制,由离散和连续预测控制组成。在每个采样周期,离散预测控制选择一组由离散的即时启用转换构成的可行序列,而连续过程计算可变预测范围内的连续常数控制动作。

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