具有挑战性的动态过程的预测函数控制使用一个简单的预稳定策略

Muhammad Saleheen Aftab, John Anthony Rossiter
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引用次数: 0

摘要

预测函数控制(PFC)是一种简单、廉价的基于模型的开环过程系统控制技术。然而,其过于简化的设计特征往往是在更具挑战性的应用中降低功效的原因;涉及轻阻尼和/或不稳定动态的过程特别难以用pfc控制。本文通过在预测函数控制公式中集成预稳定的概念,为此类应用提供了一个更可持续的解决方案。这本质上是一个两阶段的综合,在级联结构中实现预测控制之前,首先使用一种很好理解的经典方法(如比例积分导数(PID))补偿不良的开环动力学。该建议虽然对调谐和约束处理具有重要意义,但与标准PFC和PID算法相比,它在存在外部扰动的情况下提供了改进的闭环控制,如两个工业案例研究所示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Predictive functional control for challenging dynamic processes using a simple prestabilization strategy

Predictive functional control for challenging dynamic processes using a simple prestabilization strategy

Predictive functional control (PFC) is a straightforward and cheap model-based technique for systematic control of well-damped open-loop processes. Nevertheless, its oversimplified design characteristics are often the cause of diminished efficacy in more challenging applications; processes involving lightly damped and/or unstable dynamics have been particularly difficult to control with PFC. This paper presents a more sustainable solution for such applications by integrating the concept of prestabilization within the predictive functional control formulation. This is essentially a two-stage synthesis wherein the undesirable open-loop dynamics are first compensated, using a well-understood classical approach such as proportional integral derivative (PID), before implementing predictive control in a cascade structure. The proposal, although comes with significant implications for tuning and constraint handling, is, nonetheless, straightforward and provides improved closed-loop control in the presence of external perturbations compared to the standard PFC and the PID algorithms, as demonstrated with two industrial case studies.

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