Input design for hybrid system identification for accurate estimation of submodel regions
Input design for hybrid system identification for accurate estimation of submodel regions
复制标题
混合系统识别的输入设计，用于准确估计子模型区域
DOI：
10.1109/acc.2011.5990780
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
M. Yamakita
中科院分区：
文献类型：
--
作者：
Hiroshi Suzuki;M. Yamakita
本文讨论了混合系统PWARX模型辨识的输入序列设计问题。PWARX模型的辨识需要估计回归空间中的参数向量和子模型的判别面。由于我们特别关注判别表面的准确性，我们提出了一种方法来确定输入，该方法通过优化成本函数在判别表面附近生成回归向量数据。由于代价函数需要判别曲面的信息，我们提出了一种顺序识别算法，该算法交替更新模型和代价函数。通过这种方法，我们可以得到一个高精度的模型与短的输入序列。数值算例表明了该方法的有效性。
This paper addresses about designing of input sequence for identification of hybrid systems as PWARX model. Identification of PWARX model requires estimation of parameter vectors and estimation of discriminant surfaces of submodels in regressor space. Since we especially focus on accuracy of discriminant surface, we propose a method to determine input which generates regressor vector data nearby the discriminant surfaces by optimizing a cost function. Since the cost function requires information about discriminant surfaces, we propose a sequential identification algorithm, which updates the model and the cost function alternatively. By this method, we can obtain a high accurate model with short input sequence. Validity of the proposed method is illustrated in numerical examples.