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fixed-time control protocol based on fuzzy control method  (Nonlinear Dynamics)

 
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    Nonlinear Dynamics fixed-time control protocol based on fuzzy control method
    Fixed Time Control Protocol Based On Fuzzy Control Method, supplied by Nonlinear Dynamics, 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/time+based+controller/fixed+time+control+protocol+based+on+fuzzy+control+method/pm40375421-32-13-5
    Average 90 stars, based on 1 article reviews
    fixed-time control protocol based on fuzzy control method - by Bioz Stars, 2026-11
    90/100 stars

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    Article Title: Neuroadaptive fixed-time fault-tolerant containment control of high-order MIMO Nonlinear multi-agent systems in affine strict-feedback form.
    Article Snippet: A 0 Contents lists available at ScienceDirect Neural Networks journal homepage: www.elsevier.com/locate/neunet Full Length Article Neuroadaptive fixed-time fault-tolerant containment control of high-order MIMO Nonlinear multi-agent systems in affine strict-feedback formI Hui Lv, Dandan Liu, Kai Sun , Baolong Zhu ∗ School of Information and Automation, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, PR China A R T I C L E I N F O Keywords: Fixed-time containment control Fault-tolerant control Neural network Affine strict-feedback form Multi-agent systems A B S T R A C T This paper is concerned with the fixed-time containment control problem for high-order MIMO nonlinear multi-agent systems with external disturbances and actuator faults.. First, in the backstepping framework, a neuroadaptive fixed-time containment control protocol is skillfully developed under an undirected communication topology.. Second, criteria for designing desired fault-tolerant fixed-time containment control protocol are derived such that the containment performance of the resulting closed-loop MIMO multi-agent systems can be guaranteed within a fixed time horizon and avoided the singularity problem.



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    Flow chart of setting up and verification of the PBRTQC procedure. EWMA, exponentially weighted moving average; IQC, internal quality control; LIS, laboratory information system; MA, moving average; n , batch size; PBRTQC, patient‐based real‐time quality control; λ , weighting coefficient.

    Journal: Journal of Clinical Laboratory Analysis

    Article Title: Application of Patient‐Based Real‐Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening

    doi: 10.1002/jcla.25019

    Figure Lengend Snippet: Flow chart of setting up and verification of the PBRTQC procedure. EWMA, exponentially weighted moving average; IQC, internal quality control; LIS, laboratory information system; MA, moving average; n , batch size; PBRTQC, patient‐based real‐time quality control; λ , weighting coefficient.

    Article Snippet: In this light, the use of patient samples for the purpose of continuous quality control, also known as patient‐based real‐time quality control (PBRTQC), was suggested in medical laboratories by the International Federation of Clinical Chemistry (IFCC) and Laboratory Medicine PBRTQC Working Group [ ].

    Techniques: Control

    The distribution trends of truncated daily data and IQC data using the z ‐score charts. Truncated daily detection data of β‐HCG and AFP calculated by the PBRTQC EWMA intelligent procedure are plotted with green solid lines, and different levels of IQC data are shown with different colors of triangles in the z ‐score charts. The truncated daily data of analytes (A) β‐HCG and (B) AFP and the corresponding IQC data are shown in the z ‐score charts. (C) The percentage of PBRTQC accumulation CV of five analytes; TEA was the allowable total error ± 30%.

    Journal: Journal of Clinical Laboratory Analysis

    Article Title: Application of Patient‐Based Real‐Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening

    doi: 10.1002/jcla.25019

    Figure Lengend Snippet: The distribution trends of truncated daily data and IQC data using the z ‐score charts. Truncated daily detection data of β‐HCG and AFP calculated by the PBRTQC EWMA intelligent procedure are plotted with green solid lines, and different levels of IQC data are shown with different colors of triangles in the z ‐score charts. The truncated daily data of analytes (A) β‐HCG and (B) AFP and the corresponding IQC data are shown in the z ‐score charts. (C) The percentage of PBRTQC accumulation CV of five analytes; TEA was the allowable total error ± 30%.

    Article Snippet: In this light, the use of patient samples for the purpose of continuous quality control, also known as patient‐based real‐time quality control (PBRTQC), was suggested in medical laboratories by the International Federation of Clinical Chemistry (IFCC) and Laboratory Medicine PBRTQC Working Group [ ].

    Techniques:

    Early‐warning signal provided by the optimal PBRTQC EWMA procedure in the AI‐MA platform. Solid line with yellow color in the z ‐score charts represent the early‐warning signal. (A) One negative‐bias early‐warning signal of β‐HCG between June 11 and June 23, 2021. (B) One positive‐bias early‐warning signal of uE 3 between June 24 and July 1, 2021.

    Journal: Journal of Clinical Laboratory Analysis

    Article Title: Application of Patient‐Based Real‐Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening

    doi: 10.1002/jcla.25019

    Figure Lengend Snippet: Early‐warning signal provided by the optimal PBRTQC EWMA procedure in the AI‐MA platform. Solid line with yellow color in the z ‐score charts represent the early‐warning signal. (A) One negative‐bias early‐warning signal of β‐HCG between June 11 and June 23, 2021. (B) One positive‐bias early‐warning signal of uE 3 between June 24 and July 1, 2021.

    Article Snippet: In this light, the use of patient samples for the purpose of continuous quality control, also known as patient‐based real‐time quality control (PBRTQC), was suggested in medical laboratories by the International Federation of Clinical Chemistry (IFCC) and Laboratory Medicine PBRTQC Working Group [ ].

    Techniques:

    Concentration distribution of collected daily data and the corresponding IQC data. The chart of concentration frequency distribution of (A) m‐β‐HCG and (B) uE 3 from daily data. The IQC concentration of (C) m‐β‐HCG and (D) uE 3 ; L1, L2, and L3 represented the three concentration levels of IQC; Lot.1 and Lot.2 represent the IQC lot number 39190 and 89400, respectively. The daily detected data of (E) m‐β‐HCG and (F) uE 3 were transformed into the z ‐score charts by the optimal PBRTQC EWMA procedure in the AI‐MA platform.

    Journal: Journal of Clinical Laboratory Analysis

    Article Title: Application of Patient‐Based Real‐Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening

    doi: 10.1002/jcla.25019

    Figure Lengend Snippet: Concentration distribution of collected daily data and the corresponding IQC data. The chart of concentration frequency distribution of (A) m‐β‐HCG and (B) uE 3 from daily data. The IQC concentration of (C) m‐β‐HCG and (D) uE 3 ; L1, L2, and L3 represented the three concentration levels of IQC; Lot.1 and Lot.2 represent the IQC lot number 39190 and 89400, respectively. The daily detected data of (E) m‐β‐HCG and (F) uE 3 were transformed into the z ‐score charts by the optimal PBRTQC EWMA procedure in the AI‐MA platform.

    Article Snippet: In this light, the use of patient samples for the purpose of continuous quality control, also known as patient‐based real‐time quality control (PBRTQC), was suggested in medical laboratories by the International Federation of Clinical Chemistry (IFCC) and Laboratory Medicine PBRTQC Working Group [ ].

    Techniques: Concentration Assay, Transformation Assay