A controller based on Optimal Type-2 Fuzzy Logic: Systematic design, optimization and real-time implementation
A computationally-efficient systematic procedure to design an Optimal Type-2 Fuzzy Logic Controller (OT2FLC) is proposed. The main scheme is to optimize the gains of the controller using Particle Swarm Optimization (PSO), then optimize only two parameters per type-2 membership function using Genetic...
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| Main Authors: | , , , |
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| Format: | Article |
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ISA - Instrumentation, Systems, and Automation Society
2014
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908118246&doi=10.1016%2fj.isatra.2014.06.001&partnerID=40&md5=f1a42f207ee2520dd84ba1ed8ccdd3a2 http://eprints.utp.edu.my/31142/ |
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| Summary: | A computationally-efficient systematic procedure to design an Optimal Type-2 Fuzzy Logic Controller (OT2FLC) is proposed. The main scheme is to optimize the gains of the controller using Particle Swarm Optimization (PSO), then optimize only two parameters per type-2 membership function using Genetic Algorithm (GA). The proposed OT2FLC was implemented in real-time to control the position of a DC servomotor, which is part of a robotic arm. The performance judgments were carried out based on the Integral Absolute Error (IAE), as well as the computational cost. Various type-2 defuzzification methods were investigated in real-time. A comparative analysis with an Optimal Type-1 Fuzzy Logic Controller (OT1FLC) and a PI controller, demonstrated OT2FLCs superiority; which is evident in handling uncertainty and imprecision induced in the system by means of noise and disturbances. © 2014 ISA. Published by Elsevier Ltd. All rights reserved. |
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