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It tackles parameter uncertainty using imprecise reasoning. The fuzzy logic controller is usually tuned using offline methods. An online evolving adaptation of fuzzy controller design is a recent trend in fuzzy rule-based systems. The robust evolving cloud-based controller (RECCo) is one such controller implemented for single-input-single-output (SISO) systems. The membership functions and consequent rules are automatically updated in real time based on the input data. In this paper, a decentralized robust evolving cloud-based controller (DRECCo) is proposed for two-input-two-output (TITO) systems. It consists of two independent loops with RECCos having a nonparametric premise facet and an adaptive proportional-integral-derivative (PID) model consequent facet. The effectiveness of the proposed method is validated for the benchmark interacting two-tank process (ITTP) and quadruple-tank process (QTP) by simulation and in real time. The results indicate that with the information of loop pairing and the forward-acting\/reverse-acting nature of the process, the proposed controller can adapt itself to ensure set-point tracking and disturbance rejection.<\/jats:p>","DOI":"10.1177\/01423312211049237","type":"journal-article","created":{"date-parts":[[2021,10,5]],"date-time":"2021-10-05T00:42:43Z","timestamp":1633394563000},"page":"1056-1069","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Decentralized robust evolving cloud-based controller for two input two output systems"],"prefix":"10.1177","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2320-5979","authenticated-orcid":false,"given":"J","family":"Vijay Anand","sequence":"first","affiliation":[{"name":"Department of EEE, Thiagarajar College of Engineering, Madurai, 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