Results 21 to 30 of about 63,859 (262)
Robust tubes in nonlinear model predictive control
IFAC Proceedings Volumes, 2010 Abstract Nonlinear model predictive control (NMPC) strategies based on linearization about predicted system trajectories enable the online NMPC optimization to be performed by a sequence of convex optimization problems. The approach relies on bounds on linearization errors in order to ensure constraint satisfaction and convergence of the performance ...
Mark Cannon +3 more
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IEEE Access, 2019 In this study, a model predictive path tracking control method based on the prediction of tire state stiffness is proposed to improve the path tracking performance at the limit of vehicle dynamics. Considering the influence of the nonlinear properties of
Shaosong Li +4 more
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A numerically efficient fuzzy MPC algorithm with fast generation of the control signal
International Journal of Applied Mathematics and Computer Science, 2021 Model predictive control (MPC) algorithms are widely used in practical applications. They are usually formulated as optimization problems. If a model used for prediction is linear (or linearized on-line), then the optimization problem is a standard, i.e.,
Marusak Piotr M.
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IEEE Access, 2019 This paper investigates a nonlinear-model-predictive-control (NMPC)-strategy-based distributed leader-follower consensus multi-robot formation system. The control objective of this system is to design a group of nonholonomic robots to converge into the ...
Hanzhen Xiao, C. L. P. Chen
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IEEE Access, 2019 This paper proposes a vehicle stability control approach based on time-varying model predictive control to enhance the handling and stability of active front steering vehicle at the vehicle dynamics limits.
Shaosong Li +4 more
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IEEE Access, 2020 Autonomous shipping refers to the ability of a ship to independently control its own actions while transporting cargo from one port to another, which places higher requirements on ship motion control methods. When a ship enters a port, it is important to
Shijie Li +3 more
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Statistical Machine Learning in Model Predictive Control of Nonlinear Processes
Mathematics, 2021 Recurrent neural networks (RNNs) have been widely used to model nonlinear dynamic systems using time-series data. While the training error of neural networks can be rendered sufficiently small in many cases, there is a lack of a general framework to ...
Zhe Wu +3 more
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Offset-free nonlinear Model Predictive Control with state-space process models
Archives of Control Sciences, 2017 Offset-free model predictive control (MPC) algorithms for nonlinear state-space process models, with modeling errors and under asymptotically constant external disturbances, is the subject of the paper. The main result of the paper is the presentation of
Tatjewski Piotr
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Feature-Based MPPI Control with Applications to Maritime Systems
Machines, 2022 In this paper, a novel feature-based sampling strategy for nonlinear Model Predictive Path Integral (MPPI) control is presented. Using the MPPI approach, the optimal feedback control is calculated by solving a stochastic optimal control (OCP) problem ...
Hannes Homburger +3 more
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Nonlinear Model Predictive Control for Series-Parallel Hybrid Electric Buses
IEEE Access, 2019 In the trend of urgent demand of energy saving for public transportation, the series-parallel plug-in hybrid electric bus (SPPHEB) with energy saving potential is proposed.
Biao Liu +3 more
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