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Nonlinear model predictive control of energy-integrated process systems

机译:能量集成过程系统的非线性模型预测控制

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Improving energy efficiency has become particularly important in chemical processes in view of recent increases in energy prices, growing environmental concerns, and regulatory pressure. In this paper, we consider a class of process systems with significant energy recovery. Extending our previous results concerning the two time scale dynamics of such systems, we demonstrate that the fast component of the dynamics is asymptotically stable in practical cases. Using this result, we develop a hierarchical control framework, consisting of a linear control system for the fast dynamics and a MISO nonlinear model predictive controller for the slow dynamics, and prove that it guarantees exponential stability for the overall system. Subsequently, we explore the implications of this approach in economic model predictive control and optimal energy management. We illustrate our theoretical developments with a benchmark chemical process application.
机译:鉴于最近能源价格的上涨,对环境的关注和监管压力,提高能源效率在化学过程中变得尤为重要。在本文中,我们考虑一类具有显着能量回收的过程系统。扩展了我们先前关于此类系统的两个时间尺度动力学的结果,我们证明了动力学的快速分量在实际情况下是渐近稳定的。使用此结果,我们开发了一个分层控制框架,该框架由用于快速动力学的线性控制系统和用于慢速动力学的MISO非线性模型预测控制器组成,并证明它保证了整个系统的指数稳定性。随后,我们探讨了这种方法在经济模型预测控制和最佳能源管理中的意义。我们通过基准化学过程应用说明了我们的理论发展。

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