Wei Liu , Wei Tang , Huanyu Zhao , Shengyuan Xu , Ju H. Park
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引用次数: 0
Abstract
This paper studies a fuzzy finite-time preassigned performance control challenge for state-constrained non-strict feedback nonlinear systems (NSFNSs) subject to input saturation and unmatched disturbances. By incorporating barrier Lyapunov function (BLF) with finite-time performance function, a new type of preassigned performance BLF is devised to address the issues of state constraints and achieve preassigned performance metrics (PPMs). Moreover, to address the design problem for NSFNSs and estimate unmatched disturbances, a combined nonlinear disturbances observer is developed. Additionally, a command-filter backstepping method is employed in the finite-time control scheme, thereby reducing the conservativeness of the assumptions on the desired signal. With stability analyses, all control aims can be completely acquired. The proposed approach is validated through two simulation examples.
期刊介绍:
Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies.
In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.