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yalmip package  (MathWorks Inc)


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    MathWorks Inc yalmip package
    Yalmip Package, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/yalmip+package/pmc11532292-507-0-18
    Average 90 stars, based on 1 article reviews
    yalmip package - by Bioz Stars, 2026-09
    90/100 stars

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    other:

    Article Title: Observer-based fault detection and diagnosis strategy for industrial processes
    Article Snippet: This study presents the design of a fault detection and diagnosis (FDD) scheme, composed from a bank of two types of observers, applied to linear parameter varying (LPV) systems.. The first one uses a combination of reduced-order LPV observers to detect, isolate and estimate actuators faults, and the second one consists of a set of full-order LPV unknown input observers (UIO) to detect, isolate and estimate sensors faults.. The observers’ design, convergence and its stability conditions are guaranteed in terms of linear matrix inequalities (LMI).

    Article Title: Nonlinear and locally optimal controllers design for input affine locally controllable systems
    Article Snippet: With P0 we check the corresponding LMI condition in (5) employing the Yalmip package (Löfberg 2004) in Matlab in combination with the solver Sedumi (Sturm 1999).

    Software:

    Article Title: Conjunctive optimal operation of water and power networks
    Article Snippet: MATLAB© version 2019b was used for coding the optimization problems and obtaining solutions. .. YALMIP package (an open-source software package, available at https://yalmip.github.io/ ) was used for coding the optimization problem into MATLAB©. ..

    Plasmid Preparation:

    Article Title: Nonlinear and locally optimal controllers design for input affine locally controllable systems
    Article Snippet: The matrix P1¼H(V1)(0) is given as P1 7:40 13:25 23:08 6:57 13:25 27:64 47:59 13:81 23:08 47:59 85 23:93 6:57 13:81 23:93 6:96 2 666664 3 777775: ð42Þ Using (42) and Theorem 2.3, the existence of a vector Km solution of LMI (5) with F, G given in (38) has to be verified. .. Employing the Yalmip package (Löfberg 2004) in Matlab in combination with the solver2 Sedumi (Sturm 1999), it is shown that a vector Km does not exist with these data. ..



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    PSS representation of different degrees of the mulistationarity region of the network of Example 3.4 inside the hyperrectangle \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$B=[(0.0005,0),(0.001,2)]$$\end{document} B = [ ( 0.0005 , 0 ) , ( 0.001 , 2 ) ] using the information we got from the sampling representation of the multistationairy region. The orange colored points are the points with three steady states and their union is considered as approximation of K . The yellow colored area is the difference of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$U(p)-K$$\end{document} U ( p ) - K . One expects to see that this difference is getting smaller as the degree increases. However, the Matlab code that we wrote <t>using</t> <t>YALMIP</t> and <t>SeDuMi</t> does not behave as expected. a – c gives the PSS representation of the original problem of degrees 2, 6 and 10 respectively. d – f gives the PSS representation of those degrees for the problem after after rescaling the parameters for better numerical behavior via YALMIP and SeDuMi
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    PSS representation of different degrees of the mulistationarity region of the network of Example 3.4 inside the hyperrectangle \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$B=[(0.0005,0),(0.001,2)]$$\end{document} B = [ ( 0.0005 , 0 ) , ( 0.001 , 2 ) ] using the information we got from the sampling representation of the multistationairy region. The orange colored points are the points with three steady states and their union is considered as approximation of K . The yellow colored area is the difference of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$U(p)-K$$\end{document} U ( p ) - K . One expects to see that this difference is getting smaller as the degree increases. However, the Matlab code that we wrote using YALMIP and SeDuMi does not behave as expected. a – c gives the PSS representation of the original problem of degrees 2, 6 and 10 respectively. d – f gives the PSS representation of those degrees for the problem after after rescaling the parameters for better numerical behavior via YALMIP and SeDuMi

    Journal: BMC Bioinformatics

    Article Title: Polynomial superlevel set representation of the multistationarity region of chemical reaction networks

    doi: 10.1186/s12859-022-04921-6

    Figure Lengend Snippet: PSS representation of different degrees of the mulistationarity region of the network of Example 3.4 inside the hyperrectangle \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$B=[(0.0005,0),(0.001,2)]$$\end{document} B = [ ( 0.0005 , 0 ) , ( 0.001 , 2 ) ] using the information we got from the sampling representation of the multistationairy region. The orange colored points are the points with three steady states and their union is considered as approximation of K . The yellow colored area is the difference of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$U(p)-K$$\end{document} U ( p ) - K . One expects to see that this difference is getting smaller as the degree increases. However, the Matlab code that we wrote using YALMIP and SeDuMi does not behave as expected. a – c gives the PSS representation of the original problem of degrees 2, 6 and 10 respectively. d – f gives the PSS representation of those degrees for the problem after after rescaling the parameters for better numerical behavior via YALMIP and SeDuMi

    Article Snippet: These sub-rectangles are colored orange in Fig. . We use the YALMIP and SeDuMi packages of Matlab to solve the SOS optimization discussed before this example.

    Techniques: Sampling