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A controller based on Optimal Type-2 Fuzzy Logic: Systematic design, optimization and real-time implementation
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DOI：10.1016/j.isatra.2014.06.001.png)
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Abstract
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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 OT2FLC's superiority; which is evident in handling uncertainty and imprecision induced in the system by means of noise and disturbances. (C) 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Keywords:
Intelligent control
Type-2 Fuzzy Logic
Fuzzy Logic Control
Optimization
Robotic arm
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