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This paper is focused on the issue of scheduling stabilization of Takagi–Sugeno fuzzy control systems by the aid of digging down much deeper of implicit information in the underlying systems. An event-triggered real-time scheduler that decides which control mode should be executed at any given instant is constructed by periodically evaluating the joint-distribution-type of multi-instant normalized fuzzy weighting functions at every sampled instant. Profiting from the proposed event-triggered scheduling policy, the proper control mode for the current instant is updated in order to adapt time-varying situations once if the underlying joint-distribution-type changes, and thus previous implementations of control tasks with an unchanged control mode can be further relaxed in this paper. The effectiveness of our approach is verified by several simulation examples in the end. [ABSTRACT FROM AUTHOR]

This study addresses the problem of releasing the conservatism of stability criteria for continuous-time T–S fuzzy systems on the basis of an extended approach. Recently, previous stability conditions have been relaxed by exploring the positive and negative properties of the time derivatives of normalized fuzzy weighting functions but the underlying approach is not very mature. By modeling the membership space of the time derivatives of normalized fuzzy weighting functions via selected binary numbers and decimal numbers, their positive and negative properties are more fully considered and some redundant terms are transformed as a positive role instead of being simply removed. Thus, less conservative stability criteria can be achieved. Finally, the effectiveness of the proposed approach is illustrated by numerical experiments. [ABSTRACT FROM AUTHOR]

In this paper, the problem of observer-based output feedback control design of discrete-time Takagi–Sugeno (T–S) fuzzy systems is investigated based on a multi-samples method. In order to ameliorate the existing results in the literature, a fuzzy observer-based output feedback controller, which relies on multi-samples normalized fuzzy weighting functions, is developed for relaxing the design conditions of observer-based output feedback control. Moreover, thanks to the special form of the developed observer-based output feedback controller, it is shown that all the designed parameters can be solved via a set of strict linear matrix inequalities, i.e., the drawback induced by the usual two-step method is resolved by means of a compromising way. Finally, the benefit of the proposed result is validated by using some numerical experiments. [ABSTRACT FROM AUTHOR]