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An Alternative Structure of Predictive Functional Control Based on Second-Order plus Lag Time Model

机译:基于二阶加滞后时间模型的预测功能控制的替代结构

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The traditional predictive functional control usually used a first-order plus lag time prediction model to descript the process object that usually has the characteristics of high order plus large lag time or nonlinear, etc. because of the complexity to deduce the control law, so that the application of the predictive functional control is restricted in an intrinsic structure that makes tuning not only more complex than necessary, but also less transparent with respect to the key attributes of the overall controller performance, namely:' robustness, setpoint tracking, and disturbance rejection. In this paper, second-order plus lag time prediction model is used against the problem mentioned above, and the control law is deduced through the solution of generalized Fibonacci sequence, which supplies an alternative control structure of predictive functional control. Some specification parameters of the proposed control scheme are related directly to the controller performance attributes, and have arisen naturally from the formulation in a manner. The results from simulation have shown that when the second-order plus lag time prediction model is used, the performance of dynamic response of the controller is improved significantly both in set-point tracking and disturbance rejection.
机译:传统的预测功能控制通常使用一阶加滞后时间预测模型来描述通常具有高阶加大滞后时间或非线性等特征的过程对象,因为其推导控制律的复杂性,使得预测功能控制的应用受到一个固有结构的限制,该结构不仅使调节变得比必要的更为复杂,而且就整体控制器性能的关键属性(即:鲁棒性,设定点跟踪和干扰抑制)而言,其透明度也有所降低。针对上述问题,本文采用二阶加滞后时间预测模型,通过广义斐波那契数列的解来推导控制律,从而为预测功能控制提供了一种可替代的控制结构。所提出的控制方案的一些规格参数与控制器性能属性直接相关,并且自然地从某种形式上由公式产生。仿真结果表明,使用二阶加滞后时间预测模型时,控制器的动态响应性能在设定点跟踪和干扰抑制方面均得到显着改善。

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