Synchronous and Asynchronous Iterative Learning Strategies of T-S Fuzzy Systems With Measurable and Unmeasurable State Information

abstract

• 1993-2012 IEEE. By designing synchronous and asynchronous iterative learning controllers, the tracking problem of Takagi-Sugeno (T-S) fuzzy systems with measurable and unmeasurable state information is investigated in this paper. The T-S fuzzy model is first constructed to describe dynamic systems with a variable structure. Iterative learning controllers are then designed to achieve the tracking problem of T-S fuzzy systems. Here, the iterative learning controllers are designed to be synchronous and asynchronous. Also, system states are considered to be measurable and unmeasurable due to the capability of transmission bandwidth of networks and external and/or internal disturbances. Finally, simulation results are given to illustrate the usefulness of the developed criteria.

authors

• Huang, Tingwen

published proceedings

• IEEE TRANSACTIONS ON FUZZY SYSTEMS

author list (cited authors)

• Xiong, W., Xu, L., Ho, D., Cao, J., & Huang, T.

citation count

• 16

complete list of authors

• Xiong, Wenjun||Xu, Long||Ho, Daniel WC||Cao, Jinde||Huang, Tingwen

publication date

• October 2018

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE transactions on fuzzy systems  Journal

keywords

• Asynchronous Iterative Learning Controllers
• Measurable And Unmeasurable State Information
• Synchronous Iterative Learning Controllers
• Takagi-sugeno (t-s) Fuzzy Systems

Digital Object Identifier (DOI)

• 10.1109/TFUZZ.2017.2787156

start page

• 3042

end page

• 3053

volume

• 26

issue

• 5

URL

• http://dx.doi.org/10.1109/tfuzz.2017.2787156