@inproceedings{1928e9e01a1b40feb4957836a04b59d7,
title = "A Study of TSK Inference Approaches for Control Problems",
abstract = "Fuzzy inference systems provide a simple yet powerful solution to complex non-linear problems, which have been widely and successfully applied in the control field. The TSK-based fuzzy inference approaches, such as the convention TSK, interval type 2 (IT2) TSK and their extensions TSK+ and IT2 TSK+ approaches, are more convenient to be employed in the control field, as they directly produce crisp outputs. This paper systematically reviews those four TSK-based inference approaches, and evaluates them empirically by applying them to a well-known cart centering control problem. The experimental results confirm the power of TSK+ and IT2 TSK+ approaches in enhancing the inference using either dense or sparse rule bases.",
keywords = "Fuzzy control, Fuzzy inference, Sparse rule base, TSK, TSK+",
author = "Jie Li and Fei Chao and Longzhi Yang",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-27538-9_17",
language = "English",
isbn = "9783030275372",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "195--207",
editor = "Haibin Yu and Jinguo Liu and Lianqing Liu and Yuwang Liu and Zhaojie Ju and Dalin Zhou",
booktitle = "Intelligent Robotics and Applications - 12th International Conference, ICIRA 2019, Proceedings",
address = "Germany",
note = "12th International Conference on Intelligent Robotics and Applications, ICIRA 2019 ; Conference date: 08-08-2019 Through 11-08-2019",
}