$mathcal {L}_{1}$ A Fuzzy Lyapunov Function Approach to Positive Ll Observer Design for Positive Fuzzy Semi-Markovian Switching Systems With Its Application
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A Fuzzy Lyapunov Function Approach to Positive Ll Observer Design for Positive Fuzzy Semi-Markovian Switching Systems With Its Application

机译:一种模糊Lyapunov函数方法对正模糊半市场开关系统的正面LL观测器设计

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This paper concerns a positive $mathcal {L}_{1}$ observer for positive nonlinear semi-Markovian switching systems (MSSs) via the expansion of Taylor formula and the fuzzy Lyapunov function approach, in which semi-Markovian switching parameters, positivity, Takagi–Sugeno (T–S) fuzzy, and external disturbance are all considered in a unified framework. A fuzzy Lyapunov function approach with less conservativeness is introduced into the research of positive systems. In the system under consideration, positive S-MSSs with the semi-Markovian process can describe more complex systems in a practical control process. The main motivation of this paper is that the practical system subject to positivity and abrupt changes can be described by positive nonlinear S-MSSs, which always needs to consider the external disturbance. First, by using the normalized membership function approach, positive nonlinear S-MSSs can be represented by local positive T–S fuzzy S-MSSs. Second, by constructing the fuzzy Lyapunov function, some sufficient conditions are proposed for stochastic stability and $mathcal {L}_{1}$ -gain performance analysis, respectively. Then, a positive $mathcal {L}_{1}$ observer in a novel standard linear programming condition is designed to guarantee the resulting closed–loop augmented system is positive and stochastically stable with a required $mathcal {L}_{1}$ -gain performance. Finally, a practical example about the epidemiological model is introduced to show the effectiveness of the main theory.
机译:本文涉及正面<内联公式XMLNS:MML =“http://www.w3.org/1998/math/mathml”xmlns:xlink =“http://www.w3.org/1999/xlink”> $ mathcal {l} _ {1} $ 通过泰勒的扩展,正非线性半市场开关系统(MSS)的观察者公式和模糊Lyapunov函数方法,其中半月形开关参数,积极性,Takagi-Sugeno(T-S)模糊,外部干扰都在统一的框架中考虑。阳性系统的研究介绍了具有较少保守性的模糊Lyapunov功能方法。在正在考虑的系统中,具有半马克洛维亚进程的正面S-MSS可以在实际控制过程中描述更复杂的系统。本文的主要动机是,经过积极性和突然变化的实际系统可以由正非线性S-MSS描述,这始终需要考虑外部干扰。首先,通过使用归一化的隶属函数方法,正非线性S-MSS可以由局部正T-S模糊S-MSS表示。其次,通过构建模糊Lyapunov函数,提出了一些足够的条件,用于随机稳定性和 $ mathcal {l} _ {1} $ -gain性能分析, 分别。然后,一个正面<内联公式XMLNS:mml =“http://www.w3.org/1998/math/mathml”xmlns:xlink =“http://www.w3.org/1999/xlink”> < Tex-Math符号=“乳胶”> $ mathcal {l} _ {1} $ Observer在新颖的标准线性编程条件下旨在保证所产生的闭环增强系统是正面且随机性的稳定性,具有所需的<内联公式XMLNS:MML =“http://www.w3.org/1998/math/mathml”xmlns:xlink =“http://www.w3.org/1999 / xlink“> $ Mathcal {l} _ {1} $ -gain性能。最后,引入了关于流行病学模型的实际示例,以显示主要理论的有效性。

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