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