Design of Control Systems based on Data-Matching Using Input-Output Measurements

我们考虑了几个重要的问题与设计一个未知的植物基于输入/输出测量的闭环系统。主要研究结果如下：1.我们提出了一种直接的方法来获得所需的控制器的参数，通过控制器识别的输入/输出测量和期望的响应，而不是模型识别的植物。所提出的方法是现有方法的扩展，即，VRFT和FRIT。所提出的方法的一个显着特点是能够检测到意外的闭环不稳定通过使用识别误差.我们解决了FRIT获得的参数的最优性的问题，并提供了理论结果，应用预滤波器使我们能够获得实际的最佳参数，实现最佳的跟踪性能。基于这一理论结果，我们还将FRIT方法扩展为更实用的方法，即优化可以在线性计算中进行，这意味着这里得到的结果可以通过更简单的计算来检验.本文提出了基于控制器整定的系统辨识的新概念--“通过控制器辨识辨识被控对象”。也就是说，通过调整控制器，包括一个植物的结构，我们有一个最佳的植物参数反映的信息的数据和给定的规格.我们已经解决了现有的规范控制器和建议FRIT之间的连接。我们在我们的框架中重新制定了规范控制器。因此，我们已经改进了FRIT，在这个意义上，FRIT中完成的调谐方法从理论的角度产生了拟合数据和给定规格的参数。5.我们已经扩展了所提出的方法，以获得一个单一的控制器，一致地实现控制性能下植物动态变化。

We consider several important issues concerned with designing a closed loop system for an unknown plant based on input/output measurements. The main results are as follows.1. We have proposed a direct method to obtain parameters of the desired controller via controller identification from the input/output measurements and the desired response instead of model identification of the plant. The proposed method is an extension of the existing method, i.e., VRFT and FRIT. A salient feature of the proposed method is to be able to detect unexpected closed loop instability by using identification error.2. We addressed the issues on the optimality of the parameter obtained FRIT, and have provided the theoretical result that applying a prefilter enables us to obtain the actual optimal parameter for the achievement of the optimal tracking performance. Based on this theoretical result, we have also expanded FRIT into more practical method in the sense that the optimization can be performed in the linear computation, which implies that the result obtained here can be examined by more simple computation.3. We have proposed a new concept "identification of a plant via controller identification" of system identification based on controller tuning. That is, by tuning a controller including the structure of a plant, we have an optimal parameter of the plant reflecting the information of the data and the given specification.4. We have addressed the connection between an existing canonical controller and proposed FRIT. We have reformulated canonical controllers in our framework. As a result, we have refined FRIT in the sense that the tuning method done in FRIT yields the parameter fitting the data and the given specification from the theoretical points of view.5. We have extended the proposed method to obtain a single controller which uniformly achieves control performance under plant dynamics variation.