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model predictive control toolbox  (MathWorks Inc)


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    Structured Review

    MathWorks Inc model predictive control toolbox
    Model Predictive Control Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 95/100, based on 362 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/model+predictive+control/Model+Predictive+Control+Toolbox/pm41775184-154-10-9
    Average 95 stars, based on 362 article reviews
    model predictive control toolbox - by Bioz Stars, 2026-09
    95/100 stars

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    Related Articles

    Generated:

    Article Title: High speed functional imaging with a microfluidics-compatible open-top light-sheet microscope enabled by model predictive control of a tunable lens
    Article Snippet: .. Finally, we used the generated model to construct a model predictive controller using the MATLAB Model Predictive Control toolkit. ..

    Construct:

    Article Title: High speed functional imaging with a microfluidics-compatible open-top light-sheet microscope enabled by model predictive control of a tunable lens
    Article Snippet: .. Finally, we used the generated model to construct a model predictive controller using the MATLAB Model Predictive Control toolkit. ..

    Control:

    Article Title: High speed functional imaging with a microfluidics-compatible open-top light-sheet microscope enabled by model predictive control of a tunable lens
    Article Snippet: .. Finally, we used the generated model to construct a model predictive controller using the MATLAB Model Predictive Control toolkit. ..

    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: .. To quantify the relative efficacy of the proposed Hybrid GANR approach, it was benchmarked against three advanced control strategies—Adaptive PID, Fuzzy Logic Controller (FLC), and Model Predictive Control (MPC)—using identical thermal load and drive cycle datasets within MATLAB/Simulink. ..

    Article Title: Multidimensional performance trade-offs in bipedal standing of common chimpanzees and implications for human bipedal evolution
    Article Snippet: MATLAB Test version: 1.0 (R2023a) , https://www.mathworks.com , N/A. .. Model Predictive Control Toolbox version: 8.1 (R2023a) , https://www.mathworks.com , N/A. .. Model-Based Calibration Toolbox version: 5.14 (R2023a) , https://www.mathworks.com , N/A.

    Article Title: Improvement of Drone Gimbal System Performance Using a Parallel Structure of Explicit Model Predictive Control and Adaptive Neuro-Fuzzy Inference System
    Article Snippet: .. The designed controller operates independently without relying on the Model Predictive Control Toolbox of Matlab/Simulink® and is applied to the drone gimbal system. ..

    Article Title: Automated administration of medical oxygen using model predictive control incorporating real-time monitoring of breathing parameters.
    Article Snippet: .. The MPC controller implements standard finite-horizon state-space MPC using MATLAB's Model Predictive Control Toolbox (R2022b), which solves the optimal control problem via numerical quadratic programming (QP) with active-set methods. ..

    Article Title: Improvement of Drone Gimbal System Performance Using a Parallel Structure of Explicit Model Predictive Control and Adaptive Neuro-Fuzzy Inference System
    Article Snippet: .. In this study, the F , G, H , and K matrices are computed using the Model Predictive Control Toolbox in Matlab/Simulink® [46]. ..



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    95
    MathWorks Inc model predictive control toolkit
    Open-top light-sheet microscope with electrically tunable lens (ETL) remote focusing under model <t>predictive</t> control. (a) Scan methods for volumetric light-sheet imaging. (i) In the simplest case, a sample is scanned through a static sheet. (ii) An actuated objective lens can follow a scanning light-sheet, which is faster than (i) but inertia limited and can cause problems with water immersion. (iii) Remote focusing optically shifts the focal plane using an active element like an ETL (b). This setup has less inertia and no moving parts at the sample. (c) Long-working distance open-top imaging is achieved using an asymmetric pair of objective lenses coupled with a water immersion fitting. This enables unobstructed imaging across a water-matched barrier such as FEP (above). (d) Maximum intensity projections along the Z (top) and Y (bottom) axes of a worm expressing a pan-neuronal nuclear-localized fluorescent protein positioned in a microfluidic channel as shown in (c). Scale bar 20 µ m. (e) Fast actuation of an ETL induces high frequency oscillation which slows response time. Performance is improved by using model predictive control to optimize drive signals. The controller iteratively optimizes the input signal to the ETL by minimizing simulated output error while obeying system constraints.
    Model Predictive Control Toolkit, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/model+predictive+control/Model+Predictive+Control+Toolbox/bio_rxiv__2025__07__23__666439-99-15-14
    Average 95 stars, based on 1 article reviews
    model predictive control toolkit - by Bioz Stars, 2026-09
    95/100 stars
      Buy from Supplier

    Image Search Results


    Open-top light-sheet microscope with electrically tunable lens (ETL) remote focusing under model predictive control. (a) Scan methods for volumetric light-sheet imaging. (i) In the simplest case, a sample is scanned through a static sheet. (ii) An actuated objective lens can follow a scanning light-sheet, which is faster than (i) but inertia limited and can cause problems with water immersion. (iii) Remote focusing optically shifts the focal plane using an active element like an ETL (b). This setup has less inertia and no moving parts at the sample. (c) Long-working distance open-top imaging is achieved using an asymmetric pair of objective lenses coupled with a water immersion fitting. This enables unobstructed imaging across a water-matched barrier such as FEP (above). (d) Maximum intensity projections along the Z (top) and Y (bottom) axes of a worm expressing a pan-neuronal nuclear-localized fluorescent protein positioned in a microfluidic channel as shown in (c). Scale bar 20 µ m. (e) Fast actuation of an ETL induces high frequency oscillation which slows response time. Performance is improved by using model predictive control to optimize drive signals. The controller iteratively optimizes the input signal to the ETL by minimizing simulated output error while obeying system constraints.

    Journal: bioRxiv

    Article Title: High speed functional imaging with a microfluidics-compatible open-top light-sheet microscope enabled by model predictive control of a tunable lens

    doi: 10.1101/2025.07.23.666439

    Figure Lengend Snippet: Open-top light-sheet microscope with electrically tunable lens (ETL) remote focusing under model predictive control. (a) Scan methods for volumetric light-sheet imaging. (i) In the simplest case, a sample is scanned through a static sheet. (ii) An actuated objective lens can follow a scanning light-sheet, which is faster than (i) but inertia limited and can cause problems with water immersion. (iii) Remote focusing optically shifts the focal plane using an active element like an ETL (b). This setup has less inertia and no moving parts at the sample. (c) Long-working distance open-top imaging is achieved using an asymmetric pair of objective lenses coupled with a water immersion fitting. This enables unobstructed imaging across a water-matched barrier such as FEP (above). (d) Maximum intensity projections along the Z (top) and Y (bottom) axes of a worm expressing a pan-neuronal nuclear-localized fluorescent protein positioned in a microfluidic channel as shown in (c). Scale bar 20 µ m. (e) Fast actuation of an ETL induces high frequency oscillation which slows response time. Performance is improved by using model predictive control to optimize drive signals. The controller iteratively optimizes the input signal to the ETL by minimizing simulated output error while obeying system constraints.

    Article Snippet: Finally, we used the generated model to construct a model predictive controller using the MATLAB Model Predictive Control toolkit.

    Techniques: Microscopy, Control, Imaging, Expressing