Abstract
Control loop performance assessment (CPA) is essential in the operation of industrial systems. In this paper, the shortcomings of existing performance assessment methods and indicators are summarized firstly, and a novel evaluation method based on generalized correntropy criterion (GCC) is proposed to evaluate the performance of non-Gaussian stochastic systems. This criterion could characterize the statistical properties of non-Gaussian random variables more fully, so it can be directly used as the assessment index. When the expected output of the given system is unknown, generalized correntropy is used to describe the similarity of two random variables in the joint space neighborhood controlled and take it as the criterion function of the identification algorithms. To estimate the performance benchmark more quickly and accurately, a hybrid-EDA (H-EDA) combined with the idea of “wading across the stream algorithm” is proposed to obtain the system parameters and disturbance noise PDF. Through the simulation of a single loop feedback control system under different noise disturbances, the effectiveness of the improved algorithm and new indexes are verified.
Highlights
With the continuous improvement of automation in the industrial process, the production process is becoming more and more complex
Control loop performance assessment (CPA) has become an essential technology to ensure the smooth progress of industrial production [1]
To overcome the instability of model updating in the iterative process, a novel estimation of distribution algorithm (EDA) based on the classic compact genetic algorithm is proposed by [27] to optimize the benchmark function ONEMAX
Summary
With the continuous improvement of automation in the industrial process, the production process is becoming more and more complex. Harris [3] proposed a CPA index based on minimum variance control (MVC) This method is regarded as a milestone in the performance assessment research, so we named the index after the researcher, Harris. Methods of system performance assessment based on MVC are very mature and has a remarkable application effect when the noise disturbance conforms to Gaussian. When the mean of error distribution is not around zero, the wrong assessment result may be caused For this case, Zhou proposed the performance index of mean-constraint, while a CPA method based on mixture correntropy was proposed by Zhang [13]. It is very promising to study the performance assessment of non-Gaussian stochastic systems by replacing entropy criterion with generalized correntropy. The closer it is to 1, the closer the system to the ideal case, indicating that the system performs better; the closer it is to 0, the worse the system performance is, even including unstable control
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