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首页> 外文期刊>International Journal of Robust and Nonlinear Control >Event-driven model predictive control of timed hybrid Petri nets
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Event-driven model predictive control of timed hybrid Petri nets

机译:定时混合Petri网的事件驱动模型预测控制

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摘要

Hybrid Petri nets represent a powerful modeling formalism that offers the possibility of integrating, in a natural way, continuous and discrete dynamics in a single net model. Usual control approaches for hybrid nets can be divided into discrete-time and continuous-time approaches. Continuous-time approaches are usually more precise, but can be computationally prohibitive. Discrete-time approaches are less complex, but can entail mode-mismatch errors due to fixed time discretization. This work proposes an optimizationbased event-driven control approach that applies on continuous time models and where the control actions change when discrete events occur. Such an approach is computationally feasible for systems of interest in practice and avoids mode-mismatch errors. In order to handle modelling errors and exogenous disturbances, the proposed approach is implemented in a closed-loop strategy based on event-driven model predictive control.
机译:混合Petri网代表了强大的建模形式,提供了以自然方式将连续和离散动力学集成到单个网模型中的可能性。混合网络的常用控制方法可以分为离散时间方法和连续时间方法。连续时间方法通常更精确,但在计算上可能会令人望而却步。离散时间方法不太复杂,但由于固定时间离散化,可能会导致模式不匹配错误。这项工作提出了一种基于优化的事件驱动控制方法,该方法适用于连续时间模型以及离散事件发生时控制动作发生变化的地方。这种方法在实践中对于感兴趣的系统在计算上是可行的,并且避免了模式不匹配错误。为了处理建模误差和外源性干扰,该方法在基于事件驱动模型预测控制的闭环策略中实现。

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