二阶离散Volterra系统的数据驱动内模控制
Data-Driven Internal Model Control of Second-Order Discrete Volterra Systems
摘要：
随着系统复杂性的增加以及操作数据的可用性不断增加，传统控制设计范式发生了变化。数据驱动控制范式提出直接从数据中描述控制器，而不是通过第一原理对系统进行建模，然后进行（基于模型的）控制设计。通过利用Willems和合作者的一个基本结果，这种方法已被成功地应用到线性系，产生许多经典的线性控制器的基于数据的公式。本文将数据驱动方法推广到一类非线性系统，即二阶离散Volterra系统。这类系统有两个主要贡献。首先，我们表明，在输入数据激励的充要条件下，基于数据的系统表示可以从输入输出数据中导出，并用于取代显式系统模型。也就是说，Willems等人的基本结果被推广到这类系统。随后推导了输出跟踪的数据驱动内模控制公式。该方法通过两个仿真例子来说明。
英文摘要：
The increase in system complexity paired with a growing availability of operational data has motivated a change in the traditional control design paradigm. Instead of modeling the system by first principles and then proceeding with a (model-based) control design, the data-driven control paradigm proposes to directly characterize the controller from data. By exploiting a fundamental result of Willems and collaborators, this approach has been successfully applied to linear systems, yielding data-based formulas for many classical linear controllers. In the present paper, the data-driven approach is extended to a class of nonlinear systems, namely second-order discrete Volterra systems. Two main contributions are made for this class of systems. At first, we show that - under a necessary and sufficient condition on the input data excitation - a data-based system representation can be derived from input-output data and used to replace an explicit system model. That is, the fundamental result of Willems et al. is extended to this class of systems. Subsequently a data-driven internal model control formula for output-tracking is derived. The approach is illustrated via two simulation examples.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
