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Nonlinear model predictive control for chemical loop processing.

机译:用于化学回路处理的非线性模型预测控制。

摘要

A control system for optimizing a chemical looping ("CL") plant includes a reduced order mathematical model ("ROM") that is designed by eliminating mathematical terms that have minimal effect on the outcome. A non-linear optimizer provides various inputs to the ROM and monitors the outputs to determine the optimum inputs that are then provided to the CL plant. An estimator estimates the values of various internal state variables of the CL plant. The system has one structure adapted to control a CL plant that only provides pressure measurements in the CL loops A and B, a second structure adapted to a CL plant that provides pressure measurements and solid levels in both loops A, and B, and a third structure adapted to control a CL plant that provides full information on internal state variables. A final structure provides a neural network NMPC controller to control operation of loops A and B.
机译:用于优化化学循环(“ CL”)工厂的控制系统包括降阶数学模型(“ ROM”),该模型通过消除对结果影响最小的数学术语来设计。非线性优化器向ROM提供各种输入,并监视输出以确定最佳输入,然后将其提供给CL设备。估计器估计CL工厂的各种内部状态变量的值。该系统具有一种结构,该结构适于控制仅在CL回路A和B中提供压力测量值的CL设备,第二结构适于CL装置,在CL回路A和B中提供压力测量值和固体液位,第三结构适于控制CL工厂的结构,该工厂提供有关内部状态变量的完整信息。最终结构提供了一个神经网络NMPC控制器来控制回路A和B的运行。

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