{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T20:36:31Z","timestamp":1777926991490,"version":"3.51.4"},"reference-count":30,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2014,3,19]],"date-time":"2014-03-19T00:00:00Z","timestamp":1395187200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering"],"published-print":{"date-parts":[[2014,7]]},"abstract":"<jats:p>In this article, a fuzzy predictive control scheme is proposed for controlling liquid level in a three-tank system in the presence of disturbances and uncertainties. The three-tank system is considered as a hybrid system, and a hybrid model of the system is obtained using the mixed logical dynamical modeling approach. Nonlinear parts of the system are linearized based on a piecewise affine linear method. Then, a model predictive control is designed based on the hybrid model and applied to the three-tank system. Although the performance of the model predictive control method is satisfactory in normal condition, it suffers from the problem of bias in output in the presence of disturbance and uncertainty. In this article, a fuzzy supervisor is utilized to adjust the main predictive controller such that the effects of disturbance and uncertainties are degraded by using zero-offset tracking. The proposed fuzzy predictive control scheme has advantages of simplicity and efficiency in normal operation, and strong robustness in the presence of disturbances and uncertainties. Simulation results demonstrate the effectiveness and superiority of the method.<\/jats:p>","DOI":"10.1177\/0959651814524948","type":"journal-article","created":{"date-parts":[[2014,3,20]],"date-time":"2014-03-20T21:23:43Z","timestamp":1395350623000},"page":"369-384","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":9,"title":["Fuzzy predictive control of three-tank system based on a modeling framework of hybrid systems"],"prefix":"10.1177","volume":"228","author":[{"given":"Morteza","family":"Sarailoo","sequence":"first","affiliation":[{"name":"Intelligent System Research Group, Electrical and Computer Engineering Department, Babol University of Technology, Babol, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Behrooz","family":"Rezaie","sequence":"additional","affiliation":[{"name":"Intelligent System Research Group, Electrical and Computer Engineering Department, Babol University of Technology, Babol, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zahra","family":"Rahmani","sequence":"additional","affiliation":[{"name":"Intelligent System Research Group, Electrical and Computer Engineering Department, Babol University of Technology, Babol, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2014,3,19]]},"reference":[{"key":"bibr1-0959651814524948","doi-asserted-by":"publisher","DOI":"10.1016\/S0005-1098(01)00059-0"},{"key":"bibr2-0959651814524948","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.1981.1102596"},{"key":"bibr3-0959651814524948","doi-asserted-by":"publisher","DOI":"10.1016\/S0005-1098(98)00178-2"},{"key":"bibr4-0959651814524948","unstructured":"Lazar M. 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