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

• Published in: Neural computing & applications Vol. 30; no. 2; pp. 331 - 353
• Main Authors: Hamza, Mukhtar Fatihu, Yap, Hwa Jen, Choudhury, Imtiaz Ahmed, Chiroma, Haruna, Kumbasar, Tufan
• Format: Journal Article
• Language: English
• Published: London Springer London 01.07.2018; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Artificial neural networks; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Controllers; Data Mining and Knowledge Discovery; Fuzzy control; Fuzzy logic; Fuzzy systems; Hybrid structures; Image Processing and Computer Vision; Neural networks; Probability and Statistics in Computer Science; Researchers; Review; Robust control; Sliding mode control; Computational intelligence algorithms; Type 2 fuzzy logic systems; Type 2 fuzzy neural network; Adaptive control; Sliding mode control
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-017-3144-z

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.