Design of a Data-Driven PID Controller Using Operating Data
Design of a Data-Driven PID Controller Using Operating Data
复制标题
使用运行数据的数据驱动 PID 控制器的设计
DOI：
10.3182/20130703-3-fr-4038.00077
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Toru Yamamoto
中科院分区：
文献类型：
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作者：
S. Wakitani;Koichiro Nishida;M. Nakamoto;Toru Yamamoto
摘要PID控制器由于控制结构简单、PID参数物理意义明确，在许多过程系统中得到了广泛的应用。在确定PID参数的方法中，虚拟参考反馈整定（VRFT）和虚拟参考迭代整定（FRIT）作为直接利用一组运行数据确定控制参数的方法，近年来受到了广泛的关注。然而，这些方法只针对线性系统，因此，这些方法的适用范围是狭窄的，因为大多数过程系统具有非线性。另一方面，数据驱动PID（DD-PID）控制器已被提出作为一种有效的方法，非线性系统。在该方法中，PID参数递归整定的基础上，一个大的数据库。此外，数据库可以在线存储新的运行数据，因此即使系统具有非线性，PID参数也可以灵活调整。然而，该方法需要大量的实验试验来获得一个初始的PID参数在一个数据库中，它已被指出是该方法的一个弱点。本文提出了一种基于FRIT的DD-PID控制器在线修正方法。根据该方法，DD-PID控制器能够仅通过使用一组操作数据来更新数据库中的PID参数的初始集合。此外，该方法还可以扩展FRIT对非线性系统的适用范围。在这项研究中，所提出的方法的有效性进行了数值模拟评估。
Abstract PID controllers have been widely used in a lot of process systems because a control structure is simple and physical meanings of PID parameters are clear. Among the methods for determining PID parameters, the VRFT (Virtual Reference Feedback Tuning) and the FRIT (Fictitious Reference Iterative Tuning) have gotten much attention as methods which determine control parameters directly by using a set of operating data in recent years. However, these methods target only linear systems, thus applicable scopes of these methods are narrow because most process systems have nonlinearity. On the other hand, a Data-Driven PID (DD-PID) controller has been proposed as an e ective method for nonlinear systems. In this method, PID parameters are recursively tuned based on a large database. Moreover, a database can store new operating data in an on-line manner, thus PID parameters are tuned flexibly even if a system has nonlinearity. However, the method needs a lot of experimental trials to obtain an initial set of PID parameters in a database, and it has been pointed out as a weak point of this method. In this research, an o -line updating method of a DD-PID controller by using the FRIT is proposed. According to this method, a DD-PID controller is able to update an initial set of PID parameters in a database by only using a set of operating data. Moreover, this method can expand applicable scopes of the FRIT to nonlinear systems. In this research, the e ectiveness of the proposed method is numerically evaluated by some simulations.