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Design and analysis of multivariable predictive control applied to an oil-water-gas separator: A polynomial approach.

机译:设计和分析应用于油水气分离器的多变量预测控制:多项式方法。

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This dissertation uses a polynomial-operator technique to study stability and performance of unconstrained multivariable predictive control. A simple and direct way to determine stability of the closed-loop system is developed.; It is shown that to guarantee stability of the closed-loop two transfer matrices must be stable. These are represented as fraction descriptions, a ratio of “numerator” and “denominator” polynomial matrices from which the poles can be determined. Because both transfer matrices possess the same denominator matrix the position of the roots of its determinant give sufficient conditions for stability of the closed-loop. Furthermore it is shown that if a coprime fraction description is done for the process transfer matrix then it is necessary and sufficient to check if the roots of the determinant of the denominator matrix lie inside the unit circle. This technique avoids the inversion of transfer matrices which is a numerically difficult task allowing the tuning of multivariable systems with many inputs and outputs.; Performance is also studied and it is proven that the system has zero offset response to step changes in the reference, a property known to be valid for the single-input single-output case. For systems with an equal number of inputs and outputs the “inversion of the plant” is also proven. In this case the weights on the input are zero and the solution to the optimization problem results in a controller that inverts the plant and the output matches the reference.; The use of a multivariable predictive control for an oil-water-gas separator is studied. The nonlinear model of the plant is linearized around a steady state and different predictive controllers are designed for it. The controller responds positively to changes in the parameters and performance objectives are pursued. Results show agreement with the simulations done for the linear model, it is concluded that predictive control is a successful control strategy for oil-water-gas separators.; This method becomes an important tool for the analysis of predictive controllers, allowing the study of the effect of tuning parameters on the behavior of the system when the constraints are removed.
机译:本文采用多项式算子技术研究了无约束多变量预测控制的稳定性和性能。开发了一种简单直接的方法来确定闭环系统的稳定性。结果表明,为了保证闭环的稳定性,两个传递矩阵必须是稳定的。这些表示为分数描述,即“分子”和“分母”多项式矩阵的比率,可从中确定极点。因为两个传递矩阵都具有相同的分母矩阵,所以其行列式根的位置为闭环的稳定性提供了充分的条件。此外还表明,如果对过程转移矩阵进行了互质分数描述,则有必要并且充分地检查分母矩阵的行列式的根是否位于单位圆内。该技术避免了传递矩阵的求逆,这是一项数字上的难题,允许对具有许多输入和输出的多变量系统进行调整。还对性能进行了研究,并证明该系统对参考中的阶跃变化具有零偏移响应,该特性对于单输入单输出情况有效。对于输入和输出数量相等的系统,“工厂倒置”也得到了证明。在这种情况下,输入的权重为零,优化问题的解决方案将导致控制器反转设备,并且输出与参考值匹配。研究了油水气分离器的多变量预测控制的使用。工厂的非线性模型围绕稳态线性化,并为此设计了不同的预测控制器。控制器对参数的变化做出积极响应,并追求性能目标。结果表明与线性模型的仿真结果吻合,结论是预测控制是油水气分离器的成功控制策略。这种方法成为分析预测控制器的重要工具,可以在消除约束时研究调整参数对系统行为的影响。

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