标题： 数据驱动预测控制策略的比较分析 显示英文标题

标题： Comparative Analysis of Data-Driven Predictive Control Strategies

摘要： 本文通过考察其理论基础、假设和应用，比较数据驱动的预测控制策略。 三种最广为认可且影响深远的方法，数据使能预测控制、Willems-Koopman 预测控制、无模型自适应预测控制被采用。 这些策略中的每一种都进行了系统回顾，并概述了支持它的主要理论。 在分析之后，提供了关于它们基本假设的讨论，强调它们对控制效果的影响。 提供了一个数值示例作为比较的基准，以实现严格性能评估。 显示英文摘要

摘要： This paper compares data-driven predictive control strategies by examining their theoretical foundations, assumptions, and applications. The three most widely recognized and consequential methods, Data Enabled Predictive Control, Willems-Koopman Predictive Control, Model-Free Adaptive Predictive Control are employed. Each of these strategies is systematically reviewed, and the primary theories supporting it are outlined. Following analysis, a discussion is provided regarding their fundamental assumptions, emphasizing their influence on control effectiveness. A numerical example is presented as a benchmark for comparison to enable a rigorous performance evaluation.