ABSTRACT

In this research, the issue of parameter estimation for control systems is considered to develop a highly efficient estimation approach for the purpose of satisfying the need of industrial process modelling. For dynamical production processes, an error objective function in accordance with the dynamically sampled data is constructed for on-line identification. In order to simulate the instantaneous response of dynamical processes, the experimental scheme of impulse responses is adopted, and the observational data of impulse responses are used as the identification experimental data. In order to acquire high accuracy and stable performance, a hierarchical least mean square method is designed by means of the decomposition technique and the hierarchical principle. Finally, the superiority of the hierarchical least mean square approach is verified by the comparison simulation experiment and the effectiveness of the hierarchical least mean square method is proved by the detailed numerical examples.

摘要

在这项研究中，控制系统的参数估计问题被认为是开发一种高效的估计方法，以满足工业过程建模的需要。对于动态生产过程，根据动态采样数据构造误差目标函数进行在线识别。为了模拟动力过程的瞬时响应，采用脉冲响应实验方案，以脉冲响应观测数据作为辨识实验数据。为了获得高精度和稳定的性能，利用分解技术和分层原理设计了一种分层最小均方方法。最后，