A survey on advancement of hybrid type 2 fuzzy sliding mode control

HAMZA M. F. , YAP H. J. , CHOUDHURY I. A. , CHİROMA H., Kumbasar T.

NEURAL COMPUTING & APPLICATIONS, vol.30, no.2, pp.331-353, 2018 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Review
  • Volume: 30 Issue: 2
  • Publication Date: 2018
  • Doi Number: 10.1007/s00521-017-3144-z
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.331-353
  • Keywords: Type 2 fuzzy logic systems, Sliding mode control, Type 2 fuzzy neural network, Computational intelligence algorithms, Adaptive control, INTERVAL TYPE-2, LOGIC SYSTEMS, CHAOTIC SYSTEMS, DESIGN, SYNCHRONIZATION, OPTIMIZATION, SETS, REDUCTION, ALGORITHM, STRATEGY


Numerous types of hybridizations between type 2 fuzzy logic system (T2FLS) and sliding mode control (SMC) have been proposed to construct an intelligent and robust controller that departs from the drawbacks of SMC and T2FLS. Recently, these hybridizations have been extended to the hybrid structures that are composed of type 2 fuzzy neural network (T2FNN) and SMC in order to produce adaptive, intelligent and robust controllers. Moreover, optimization algorithms are integrated with these controllers in order to tune/optimize their parameters for a superior control performance. In this paper, a survey of the advances on the hybridization of T2FLS, T2FNN, SMC and computational intelligence algorithms is presented. It has been observed that all the works involving T2FLS employed interval type 2 fuzzy logic systems. Despite the advantages of general type 2 fuzzy logic systems (GT2FLS), no record of applying GT2FLSs has been encountered in this domain. The trend of publications, the limitations associated with previous works and future research directions are outlined in the paper. Expert researchers can use this survey as a benchmark for proposing novel approaches while novice researchers (especially graduate students) can use this survey as a starting point.