Results 11 to 20 of about 64,076 (261)
Economic Nonlinear Model Predictive Control [PDF]
In recent years, Economic Model Predictive Control (EMPC) has received considerable attention of many research groups. The present tutorial survey summarizes state-of-the-art approaches in EMPC. In this context EMPC is to be understood as receding-horizon optimal control with a stage cost that does not simply penalize the distance to a desired ...
Timm Faulwasser +2 more
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Experimental Validation of a Guaranteed Nonlinear Model Predictive Control
This paper combines the interval analysis tools with the nonlinear model predictive control (NMPC). The NMPC strategy is formulated based on an uncertain dynamic model expressed as nonlinear ordinary differential equations (ODEs).
Mohamed Fnadi +1 more
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Modeling and model predictive control of a nonlinear hydraulic system [PDF]
This paper deals with modeling and control of a hydraulic three tank system. A process of creating a computer model in MATLAB / Simulink environment is described and optimal PID and model predictive controllers are proposed. Modeling starts with creation of an initial mathematical model based on first principles approach.
Petr Chalupa, Jakub Novák
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This paper presents nonlinear model predictive control based adaptive equivalent consumption minimization strategy for fuel cell hybrid electric bus. The proposed strategy considers the average travel speed profile of road segments in route of fuel cell ...
Jooin Lee, Hyeongcheol Lee
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Long-Horizon Nonlinear Model Predictive Control of Modular Multilevel Converters
Modular Multilevel Converters (MMCs) are a topology that can scale several voltage levels to obtain higher efficiency and lower harmonics than most voltage-source converters.
Victor Daniel Reyes Dreke, Mircea Lazar
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Lyapunov-based Model Predictive Control of Nonlinear Quadruple Tank System Using Constrained and Unconstrained Methods [PDF]
Model predictive control is a widely utilized advanced control technique in industrial settings, valued for its capacity to effectively manage complex multi-input multi-output processes while optimizing process performance.
Hossein Yektamoghaddam +3 more
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Nonlinear Predictive Control with a Gaussian Process Model [PDF]
Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can highlight areas of the input space where prediction quality is poor, due to the lack of data or its complexity, by indicating the higher variance around the predicted mean.
Jus Kocijan, Roderick Murray-Smith
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The marine boiler-turbine system is the core part for the steam-powered ships with complicated dynamics. To improve the power tracking performance and fulfill the requirement of high utilization rate of fossil energy, the control performance of the ...
Shiquan Zhao +4 more
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Controlling an automotive suspension system using an actuator is a complex nonlinear problem that requires both fast and precise solutions in order to achieve optimal performance.
Daniel Rodriguez-Guevara +4 more
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Design and verification of model predictive control for micro-turboshaft engine
In this article, a nonlinear model predictive control algorithm for a micro-turboshaft engine is designed. The control effect is verified by a bench test.
Mengwei Zhang +3 more
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