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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2848

Title: Sustainable Control System Design Using A Nonlinear Fuzzy Logic Expert System PD Controller Design Approach In Matlab/Simulink
Authors: Ezekiel, D.M.
Dagyeng, H.H.
Keywords: Heuristic
Membership functions
Issue Date: 2017
Publisher: Journal of Emerging Trends in Engineering and Applied Sciences
Series/Report no.: Vol. 8;Iss. 2; Pp 79-84
Abstract: The Nonlinear Fuzzy Logic (NFL) expert system design is another approach, like the Quantitative feedback theory (QFT), for designing a control system. The Fuzzy logic control is a formal methodology for implementing control system based on human heuristic knowledge. The fuzzy logic expert system tries to mimic an expert operator by converting crisp values into membership functions on a 2 dimensional(2D) array, 2 universes of discourse for the error (e) and the change in error (ce). The Robust design performance for the Oil Rig model-the Lab Servo Rig, in real time (online) using the matlab file (m-files) or the graphical user interface (GUI) in MATLAB is then compared with that of the SIMULINK model as well as the quantitative feedback theory QFT) approach at the end of our design. For both designs, the same plant, controller and pre-filter models and specifications are used. This paper shows that both QFT and the fuzzy logic methods systematically gave out accurate and identical outputs, suggesting that both methods are highly of practical importance and can be used in the design process of a controller.
URI: http://hdl.handle.net/123456789/2848
ISSN: 2141-7016
Appears in Collections:Electrical/Electronics Engineering

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