{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T02:13:57Z","timestamp":1771467237927,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2018,5,1]],"date-time":"2018-05-01T00:00:00Z","timestamp":1525132800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Control loop Performance Assessment (CPA) plays an important role in system operations. Stochastic statistical CPA index, such as a minimum variance controller (MVC)-based CPA index, is one of the most widely used CPA indices. In this paper, a new minimum entropy controller (MEC)-based CPA method of linear non-Gaussian systems is proposed. In this method, probability density function (PDF) and rational entropy (RE) are respectively used to describe the characteristics and the uncertainty of random variables. To better estimate the performance benchmark, an improved EDA algorithm, which is used to estimate the system parameters and noise PDF, is given. The effectiveness of the proposed method is illustrated through case studies on an ARMAX system.<\/jats:p>","DOI":"10.3390\/e20050331","type":"journal-article","created":{"date-parts":[[2018,5,3]],"date-time":"2018-05-03T03:20:27Z","timestamp":1525317627000},"page":"331","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Non-Gaussian Systems Control Performance Assessment Based on Rational Entropy"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1589-7423","authenticated-orcid":false,"given":"Jinglin","family":"Zhou","sequence":"first","affiliation":[{"name":"College of Information Science &amp;Technology, Beijing University of Chemical Technology, Beijing 100029, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiqing","family":"Jia","sequence":"additional","affiliation":[{"name":"College of Information Science &amp;Technology, Beijing University of Chemical Technology, Beijing 100029, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huixia","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Missile Engineering, Army Engineering University, Shijiazhuang 050003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuyi","family":"Fan","sequence":"additional","affiliation":[{"name":"Department of Missile Engineering, Army Engineering University, Shijiazhuang 050003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.conengprac.2016.01.008","article-title":"Control performance assessment based on sensor fusion techniques","volume":"49","author":"Khamseh","year":"2016","journal-title":"Control Eng. 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