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Open AccessArticle

Performance Assessment of Non-Gaussian Control Systems Based on Mixture Correntropy

by Jinfang Zhang * and Di Wu
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(11), 1069; https://doi.org/10.3390/e21111069
Received: 10 September 2019 / Revised: 27 October 2019 / Accepted: 29 October 2019 / Published: 31 October 2019
The performance assessment of any control system plays a key role in industrial control systems. To meet the real-time requirements of modern control systems, a quick and accurate evaluation of the performance of a system is necessary. In this paper, a performance assessment method of a non-Gaussian control system based on mixture correntropy is proposed for non-Gaussian stochastic systems. Mixture correntropy can solve the problem of minimum entropy translation invariance. When the expected output of a system is unavailable, mixture correntropy combined with the estimation of distribution algorithm (EDA) is used for system identification and noise distribution estimation so as to calculate the benchmark of entropy-based performance assessment. When the expected output of a system is available, the mixture correntropy is directly used as the index to evaluate the performance of the system. To improve the real-time aspect of the performance assessment, an improved EDA is presented to obtain the evaluation index more quickly. For both Gaussian and non-Gaussian systems, the mixture correntropy and the improved identification algorithm are used for system performance assessment, and the results are compared with the minimum entropy index and the probability density function (PDF) curve coincident area index. The comparisons verify the rationality and effectiveness of the correntropy index and the rapidity of the improved EDA algorithm. View Full-Text
Keywords: control system performance assessment; non-Gaussian; mixture correntropy; minimum entropy; EDA algorithm control system performance assessment; non-Gaussian; mixture correntropy; minimum entropy; EDA algorithm
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Zhang, J.; Wu, D. Performance Assessment of Non-Gaussian Control Systems Based on Mixture Correntropy. Entropy 2019, 21, 1069.

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