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Empirical Modeling of Control Valve Layer with Application to Model Predictive Control-Based Stiction Compensation * * Financial support from the National Science Foundation and the Department of Energy is gratefully acknowledged.

机译:控制阀层的经验建模及其在基于预测控制的静摩擦补偿中的应用 * * 美国国家科学基金会和感谢能源部。

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Abstract: In this work, we develop an empirical modeling procedure for feedback loops comprised of sticky valves and linear controllers for the valves and incorporate the models in a model predictive control (MPC)-based stiction compensation strategy. The empirical models are developed from data on the measured values of the valve outlet flowrates and the set-points for these flowrates. They utilize standard empirical model structures but are defined in a piecewise fashion, with different branches identified for set-point changes that correspond to sticking of the valve and to sliding of the valve, and modifications to account for the effect of the linear controller on the response of the valve outlet flowrate to a set-point change. Through a chemical process example, it is shown that the use of the empirical models in the MPC-based stiction compensation strategy can decrease the computation time of the method without significantly jeopardizing the constraint satisfaction of the closed-loop process, but preventing the need for a valve layer model with parameters and/or details about the valve that are difficult to obtain.
机译:摘要:在这项工作中,我们开发了由粘性阀和线性阀控制器组成的反馈回路的经验建模程序,并将模型纳入基于模型预测控制(MPC)的静力补偿策略中。经验模型是根据阀出口流量的测量值和这些流量的设定点的数据开发的。它们利用标准的经验模型结构,但以分段的方式定义,为设定点变化标识了不同的分支,这些变化对应于阀门的粘滞和阀门的滑动,并进行了修改以考虑线性控制器对阀门的影响。阀门出口流量对设定点变化的响应。通过一个化学过程示例,表明在基于MPC的静摩擦补偿策略中使用经验模型可以减少该方法的计算时间,而不会显着危害闭环过程的约束满足,但避免了需要带有难以获得的阀门参数和/或细节的阀门层模型。

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