动态数据校正技术用于GMVC控制器性能评估的改进

The improvement of dynamic data reconciliation on the GMVC-based controller performance assessment

摘要:

在实际工业生产过程中,控制器性能的好坏直接影响了系统的收益。事实上,由于工作环境的复杂性,控制器容易受到各种干扰信号的影响,这通常会导致控制效果不符合预期。因此,对控制器的性能进行评估显得尤为重要。针对反馈系统中测量噪声的干扰问题,分析了测量噪声对基于广义最小方差控制(GMVC)的控制器性能评估(CPA)结果的影响；为了提升CPA的精度,提出了一种动态数据校正(DDR)方法来降低测量噪声对系统性能的影响。首先,在SISO和MIMO系统中引入基于GMVC的CPA；接着讨论了测量噪声对CPA结果的影响；最后,采用DDR滤波器来提升CPA结果的准确性。仿真中系统在不同情况下输出的比较验证了DDR滤波器的良好性能。

Abstract:

In the actual industrial production process, the performance of the controller directly affects the revenue of the system. In fact, due to the complexity of the working environment, the controller is susceptible to various interference signals, which usually causes the control effect is not as expected. Therefore, it is particularly important to assess the performance of the controller. Aiming at the interference problem of measurement noise in feedback system, the effect of measurement noise on the results of controller performance assessment (CPA) based on generalized minimum variance control (GMVC) is analyzed. In order to improve the accuracy of CPA, a dynamic data reconciliation (DDR) method is proposed to reduce the impact of measurement noise on the system performance. Firstly, GMVC based CPA is introduced in SISO and MIMO systems, and then the influence of measurement noise on CPA results is discussed. Finally, DDR filter is used to improve the accuracy of CPA results. The comparison of the output of the system under different conditions in the simulation verifies the significant performance of DDR filter.