Computationally Efficient Nonlinear Model Predictive Control Using the L1 Cost-Function [PDF]
Sensors, 2021 Model Predictive Control (MPC) algorithms typically use the classical L2 cost function, which minimises squared differences of predicted control errors. Such an approach has good numerical properties, but the L1 norm that measures absolute values of the ...
Maciej Ławryńczuk, Robert Nebeluk
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Learning Nonlinear Dynamics of Flexible Structures for Predictive Control Using Gaussian Process NARX Models [PDF]
BiomimeticsBiological systems regulate motion and suppress unwanted vibrations through learning, adaptation, and predictive control under uncertainty. Inspired by these principles, Bayesian system identification has emerged as a powerful framework for modeling and ...
Nasser Ayidh Alqahtani
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Path Tracking of Mining Vehicles Based on Nonlinear Model Predictive Control
Applied Sciences, 2019 Path tracking of mining vehicles plays a significant role in reducing the working time of operators in the underground environment. Because the existing path tracking control of mining vehicles, based on model predictive control, is not very effective ...
Guoxing Bai +5 more
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Efficient Nonlinear Model Predictive Control of Automated Vehicles
Mathematics, 2022 In this paper, an efficient model predictive control (MPC) of velocity tracking of automated vehicles is proposed, in which a reference signal is given a priori.
Shuyou Yu +5 more
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Nonlinear Model Predictive Control of Wine Fermentation Kinetics
Engineering Proceedings, 2023 Most wine fermentations are completed in successive batches during a 2 month harvest period. Red wine fermentations are usually completed in 10 to 14 days, while white wine fermentations are completed in 21 to 24 days. The demand for resources—equipment,
James Nelson +2 more
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Steam Turbine Rotor Stress Control through Nonlinear Model Predictive Control
Energies, 2021 The current flexibility of the energy market requires operating steam turbines that have challenging operation requirements such as variable steam conditions and higher number of startups.
Stefano Dettori +6 more
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Efficient MPC algorithms with variable trajectories of parameters weighting predicted control errors [PDF]
Archives of Control Sciences, 2020 Model predictive control (MPC) algorithms brought increase of the control system performance in many applications thanks to relatively easily solving issues that are hard to solve without these algorithms.
Robert, Nebeluk, Piotr, Marusak
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Non-linear Model Predictive Control for Smart Heating of Buildings [PDF]
E3S Web of Conferences, 2021 Smart and flexible operation of components in district heating systems can play a crucial role in integrating larger shares of renewable energy sources in energy systems.
Thilker Christian Ankerstjerne +5 more
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Experimental Validation of a Guaranteed Nonlinear Model Predictive Control
Algorithms, 2021 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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IEEE Access, 2023 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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