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This particular project focuses on a complex system whose dynamics are not very well understood and hence control designs are not straightforward. The project deals with the control of industrial overhead cranes. The project has the potential of bringing many rewards to industries, which are concerned with optimising lifting equipment performance. Such a system will allow these industries to save time and consequently costs as the volume of loaded and unloaded goods increases. Part of this project is to model the system surrounding the crane system and then design a suitable algorithm for load anti-sway purposes. The objective of this project is to design and implement an intelligent based controller that can be used to assist a crane operator in the difficult parts of the operation. The designed controller should give the appropriate control signal to the crane system such that the time taken to reach the target position is minimised with a zero sway angle at the destination. Earlier part of the project consisting of analysing and improving if required the existing 3-D mathematical linear and non-linear crane models. Two different models have been investigated: one with a constant cable length and the other with a variable cable length. The implementation of the controller is based on Fuzzy Logic Control (FLC). Two types of FLC have been used and compared the Fixed FLC and the FLC based on Adaptive Neuro Fuzzy Inference System (ANFIS). Heuristic approaches have been used for tuning the Fixed FLC. Data obtained from the Fixed FLC are then used for training ANFIS FLC. The results prove that it is possible to model an off-line expert fuzzy logic controller for an overhead crane. The controller achieved satisfactorily results for a constant and a variable rope length with minimal tuning than the fixed fuzzy method. Proposals for further work are also briefly discussed.

Item Type: Thesis (Masters)
Academic Subject : Academic Department - Mechanical Engineering - Materials - Failure analysis - Fracture mechanics
Subject: T Technology > T Technology (General)
T Technology > TJ Mechanical engineering and machinery
Divisions: Engineering > Mechanical
Depositing User: Users 2053 not found.
Date Deposited: 30 Sep 2013 16:55
Last Modified: 02 Oct 2019 19:01
URI: http://utpedia.utp.edu.my/id/eprint/7795

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