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nonlinear model predictive control nmpc  (Nonlinear Dynamics)

 
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    Nonlinear Dynamics nonlinear model predictive control nmpc
    Nonlinear Model Predictive Control Nmpc, supplied by Nonlinear Dynamics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/model+predictive+controller/control+free+mfc+model/pmc12528703-115-1-21
    Average 86 stars, based on 1 article reviews
    nonlinear model predictive control nmpc - by Bioz Stars, 2026-10
    86/100 stars

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    Control:

    Article Title: A survey on fuzzy control for mechatronics applications
    Article Snippet: .. Model-Free Control (MFC) (Fliess & Join, 2009, 2013) combines the popular and widely used PI and PID controllers, as well as Proportional (P) controllers, with an intelligent term that compensates for the effects of nonlinear dynamics, disturbances, and uncertain parameters. ..

    Article Title: Cooperative modular multilevel converter control based on PSO-optimized fuzzy-PI and hierarchical finite-state model predictive control.
    Article Snippet: .. In the inner loop, finite control set model predictive control (FCS-MPC) has been widely applied to MMCs thanks to its ability to handle multivariable and nonlinear dynamics while offering fast transient response[17-19]. ..

    Article Title: Learning-Based MPC Leveraging SINDy for Vehicle Dynamics Estimation
    Article Snippet: .. Abbreviations The following abbreviations are used in this manuscript: MPC Model Predictive Control SINDy Sparse Identification of Nonlinear Dynamics RHC Receding Horizon Control SME Set Membership Estimation GP Gaussian Process BLR Bayesian Linear Regression LS Least Squares ARX Auto-Regressive with Exogenous Input DMDc Dynamic Mode Decomposition with Control LASSO Least Absolute Shrinkage and Selection Operator 3-DOF Three Degrees of Freedom NLP Nonlinear Programming SQP Sequential Quadratic Programming RTI Real-Time Iteration SIL Software In the Loop ..

    Article Title: Model-free adaptive fixed-time prescribed performance control for PEMFC air feeding system based on oxygen excess ratio reconstruction
    Article Snippet: .. Moreover, nonlinear model predictive control (NMPC) is employed for regulating airflow rate due to its ability to manage input constraints and nonlinear dynamics , , . ..

    other:

    Article Title: 40 Hz light stimulation restores early brain dynamics alterations and associative memory in Alzheimer’s disease model mice
    Article Snippet: While conventional metrics of dynamic stability from nonlinear dynamics are difficult to estimate without knowledge of governing equations , limiting their applicability in experimental neuroscience, we apply a time-resolved, model-free metric capitalizing on a recent application of extreme value statistics results to dynamical systems theory ( ).

    Selection:

    Article Title: Learning-Based MPC Leveraging SINDy for Vehicle Dynamics Estimation
    Article Snippet: .. Abbreviations The following abbreviations are used in this manuscript: MPC Model Predictive Control SINDy Sparse Identification of Nonlinear Dynamics RHC Receding Horizon Control SME Set Membership Estimation GP Gaussian Process BLR Bayesian Linear Regression LS Least Squares ARX Auto-Regressive with Exogenous Input DMDc Dynamic Mode Decomposition with Control LASSO Least Absolute Shrinkage and Selection Operator 3-DOF Three Degrees of Freedom NLP Nonlinear Programming SQP Sequential Quadratic Programming RTI Real-Time Iteration SIL Software In the Loop ..

    Software:

    Article Title: Learning-Based MPC Leveraging SINDy for Vehicle Dynamics Estimation
    Article Snippet: .. Abbreviations The following abbreviations are used in this manuscript: MPC Model Predictive Control SINDy Sparse Identification of Nonlinear Dynamics RHC Receding Horizon Control SME Set Membership Estimation GP Gaussian Process BLR Bayesian Linear Regression LS Least Squares ARX Auto-Regressive with Exogenous Input DMDc Dynamic Mode Decomposition with Control LASSO Least Absolute Shrinkage and Selection Operator 3-DOF Three Degrees of Freedom NLP Nonlinear Programming SQP Sequential Quadratic Programming RTI Real-Time Iteration SIL Software In the Loop ..



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    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.
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    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