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Online fuzzy identification for an intelligent controller based on a simple platform |
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| Authors: | Sašo Blažič Igor Škrjanc Samo Gerkšič Gregor Dolanc Stanko Strmčnik Mincho B. Hadjiski Anna Stathaki |
| Affiliation: | 1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, PR China;2. College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, PR China;3. College of Mechatronics and Control Engineering, Hubei Normal University, Huangshi 435002, PR China;4. Department of Mathematics, King Abdulaziz University, Jeddah 21589, Saudi Arabia;1. Faculty of Electrical Engineering, University of Ljubljana, Tr?a?ka 25, Ljubljana, SI-1000, Slovenia;2. Department of Knowledge-Based Mathematical Systems, Johannes Kepler University, Altenbergerstrasse 69, Linz, Austria |
| Abstract: | The paper presents the identification issues of the self-tuning nonlinear controller ASPECT (Advanced control algorithmS for ProgrammablE logiC conTrollers). The controller is implemented on a simple PLC platform with an extra mathematical coprocessor, but is intended for the advanced control of complex processes. The model of the controlled plant is obtained by means of experimental modelling. A special batch-wise algorithm that is based on the Takagi–Sugeno model and uses “fuzzy instrumental variables” technique is described in the paper. Many robustness problems of the classical adaptive approaches can be circumvented to some extent by the proposed batch-wise approach combined with a supervisory mechanism. The paper also includes some experimental results on the hydraulic pilot plant and some simulation case studies. |
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