Neural Computing and Applications

, Volume 28, Issue 5, pp 979–999 | Cite as

Recent advances on the use of meta-heuristic optimization algorithms to optimize the type-2 fuzzy logic systems in intelligent control

  • Mukhtar Fatihu Hamza
  • Hwa Jen Yap
  • Imtiaz Ahmed Choudhury
Review

Abstract

Finding the appropriate values of parameters and structure of type-2 fuzzy logic systems is a difficult and complex task. Many types of meta-heuristic algorithms have been used to find the complex structure and appropriate parameter values of the type-2 fuzzy systems and more recently hybrid meta-heuristic algorithms. In this paper, we review recent advances (2012 to date) on the application of meta-heuristic algorithms and hybrid meta-heuristic algorithms, for the optimization of type-2 fuzzy logic systems in intelligent control. It was found that the major meta-heuristic algorithms used for optimizing the design of type-2 fuzzy logic systems in intelligent control were genetic algorithms and particle swarm optimization as well as hybrid meta-heuristic algorithms. Researchers can use this review as a starting point for further advancement as well as an exploration of other meta-heuristic algorithms that have received little or no attention from researchers.

Keywords

Type-2 fuzzy logic systems Intelligent control Genetic algorithm Particle swarm optimization Hybrid meta-heuristic algorithms 

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Copyright information

© The Natural Computing Applications Forum 2015

Authors and Affiliations

  • Mukhtar Fatihu Hamza
    • 1
    • 2
  • Hwa Jen Yap
    • 1
  • Imtiaz Ahmed Choudhury
    • 1
  1. 1.Department of Mechanical EngineeringUniversity of MalayaKuala LumpurMalaysia
  2. 2.Department of Mechatronics EngineeringBayero UniversityKanoNigeria

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