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matlab simulink  (MathWorks Inc)


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    MathWorks Inc matlab simulink
    Matlab Simulink, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 885 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/simulation+modeling+tool+matlab/Simulink+Control+Design/pm37931472-77-4-5
    Average 96 stars, based on 885 article reviews
    matlab simulink - by Bioz Stars, 2026-09
    96/100 stars

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    Related Articles

    Control:

    Article Title: Efficient speed and voltage regulation of BLDC motor drive for EV applications using a multi-device interleaved DC-DC bidirectional converter with TIFDNFD-SFOA controller.
    Article Snippet: .. The design and control implementations were analyzed and simulated using the MATLAB/Simulink environment. ..

    Article Title: Predictive temperature control of electric two wheeler hub motor using gradient aware neural regulation with degradation tracking and fault tolerant multi condition torque adaptation.
    Article Snippet: .. This section presents the full state transition design of the Fallback and Safe-Mode Management System (FSMS), implemented as a Stateflow® chart within the Simulink® control environment and subsequently embedded for real-time execution on the VCU. ..

    Article Title: A novel Fibonacci sequence-based motion profile
    Article Snippet: .. To verify the effectiveness and feasibility of the motion profile design method proposed in this paper, a unified closed-loop velocity control model was established in MATLAB/Simulink. ..

    Article Title: Fault Detection and Monitoring in Induction Machines Using Data-Driven Model Drift Detection
    Article Snippet: The motor is driven by a custom-designed Variable Speed Drive (VSD) developed at the university laboratory, which utilizes a Texas Instruments TMS320F28388D DSP to command a two-level voltage-source inverter. .. Regarding the software implementation, MATLAB R2024a and Simulink 24.1 were used to design, compile, and deploy the discrete-time control algorithms onto the VSD’s embedded processor. ..

    Article Title: Fault Detection and Monitoring in Induction Machines Using Data-Driven Model Drift Detection.
    Article Snippet: The motor is driven by a custom-designed Variable Speed Drive (VSD) developed at the university laboratory, which utilizes a Texas Instruments TMS320F28388D DSP to command a two-level voltage-source inverter. .. Regarding the software implementation, MATLAB R2024a and Simulink 24.1 were used to design, compile, and deploy the discrete-time control algorithms onto the VSD’s embedded processor. ..

    Software:

    Article Title: Fault Detection and Monitoring in Induction Machines Using Data-Driven Model Drift Detection
    Article Snippet: The motor is driven by a custom-designed Variable Speed Drive (VSD) developed at the university laboratory, which utilizes a Texas Instruments TMS320F28388D DSP to command a two-level voltage-source inverter. .. Regarding the software implementation, MATLAB R2024a and Simulink 24.1 were used to design, compile, and deploy the discrete-time control algorithms onto the VSD’s embedded processor. ..

    Article Title: Fault Detection and Monitoring in Induction Machines Using Data-Driven Model Drift Detection.
    Article Snippet: The motor is driven by a custom-designed Variable Speed Drive (VSD) developed at the university laboratory, which utilizes a Texas Instruments TMS320F28388D DSP to command a two-level voltage-source inverter. .. Regarding the software implementation, MATLAB R2024a and Simulink 24.1 were used to design, compile, and deploy the discrete-time control algorithms onto the VSD’s embedded processor. ..



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    The minimal physiologically‐based pharmacokinetic ( mPBPK ) models that are used in ATLAS mPBPK. ( a ) mPBPK model for small molecules. ( b ) mPBPK model for large molecules with no target binding. ( c ) mPBPK model for large molecules with target binding in plasma (interstitial fluid). ( d ) mPBPK model for large molecules with target binding in peripheral tissues. Parameters' names and typical values are shown in Table . EV, extravascular; IV, intravenous; PO, oral.

    Journal: CPT: Pharmacometrics & Systems Pharmacology

    Article Title: ATLAS mPBPK: A MATLAB‐Based Tool for Modeling and Simulation of Minimal Physiologically‐Based Pharmacokinetic Models

    doi: 10.1002/psp4.12441

    Figure Lengend Snippet: The minimal physiologically‐based pharmacokinetic ( mPBPK ) models that are used in ATLAS mPBPK. ( a ) mPBPK model for small molecules. ( b ) mPBPK model for large molecules with no target binding. ( c ) mPBPK model for large molecules with target binding in plasma (interstitial fluid). ( d ) mPBPK model for large molecules with target binding in peripheral tissues. Parameters' names and typical values are shown in Table . EV, extravascular; IV, intravenous; PO, oral.

    Article Snippet: In this tutorial, we present a MATLAB‐based tool for the modeling and simulation of mPBPK models (ATLAS mPBPK).

    Techniques: Binding Assay, Clinical Proteomics

    Concordance of simulated ATLAS mPBPK small‐molecule model values based on pharmacokinetic data of beta‐lactams. Figure is not an output of ATLAS mPBPK but was constructed by processing ATLAS mPBPK simulation output using MATLAB.

    Journal: CPT: Pharmacometrics & Systems Pharmacology

    Article Title: ATLAS mPBPK: A MATLAB‐Based Tool for Modeling and Simulation of Minimal Physiologically‐Based Pharmacokinetic Models

    doi: 10.1002/psp4.12441

    Figure Lengend Snippet: Concordance of simulated ATLAS mPBPK small‐molecule model values based on pharmacokinetic data of beta‐lactams. Figure is not an output of ATLAS mPBPK but was constructed by processing ATLAS mPBPK simulation output using MATLAB.

    Article Snippet: In this tutorial, we present a MATLAB‐based tool for the modeling and simulation of mPBPK models (ATLAS mPBPK).

    Techniques: Construct

    Demonstration of ATLAS mPBPK large‐molecule model based on PK data of Trastuzumab (target binding in peripheral tissues) and Mavrillimumab (target binding in plasma) for a range of doses. Figures are not an output of ATLAS mPBPK but were constructed by processing ATLAS mPBPK simulation output using MATLAB. c‐TMDD, Target mediated drug disposition in plasma (central); hr, hour; mPBPK, minimal physiologically‐based pharmacokinetic modeling; p‐TMDD, target‐mediated drug disposition in peripheral tissues.

    Journal: CPT: Pharmacometrics & Systems Pharmacology

    Article Title: ATLAS mPBPK: A MATLAB‐Based Tool for Modeling and Simulation of Minimal Physiologically‐Based Pharmacokinetic Models

    doi: 10.1002/psp4.12441

    Figure Lengend Snippet: Demonstration of ATLAS mPBPK large‐molecule model based on PK data of Trastuzumab (target binding in peripheral tissues) and Mavrillimumab (target binding in plasma) for a range of doses. Figures are not an output of ATLAS mPBPK but were constructed by processing ATLAS mPBPK simulation output using MATLAB. c‐TMDD, Target mediated drug disposition in plasma (central); hr, hour; mPBPK, minimal physiologically‐based pharmacokinetic modeling; p‐TMDD, target‐mediated drug disposition in peripheral tissues.

    Article Snippet: In this tutorial, we present a MATLAB‐based tool for the modeling and simulation of mPBPK models (ATLAS mPBPK).

    Techniques: Binding Assay, Clinical Proteomics, Construct