Results 11 to 20 of about 22,130,080 (237)
Gaussian process model based predictive control [PDF]
, 2004 Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of non-linear dynamic systems. The Gaussian processes can highlight areas of the input space where prediction quality is poor, due to the lack ...
Rasmussen, C.E. +3 more
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Model Predictive Control, Cost Controllability, and Homogeneity [PDF]
SIAM Journal on Control and Optimization, 2020 We are concerned with the design of Model Predictive Control (MPC) schemes such that asymptotic stability of the resulting closed loop is guaranteed even if the linearization at the desired set point fails to be stabilizable. Therefore, we propose to construct the stage cost based on the homogeneous approximation and rigorously show that applying MPC ...
Coron, Jean-Michel +2 more
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Model Predictive Impedance Control [PDF]
2020 IEEE International Conference on Robotics and Automation (ICRA), 2020 Robots are more and more often designed in order to perform tasks in synergy with human operators. In this context, a current research focus for collaborative robotics lies in the design of high-performance control solutions, which ensure security in spite of unmodeled external forces.
Maciej Bednarczyk +2 more
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Multiplexed model predictive control [PDF]
Automatica, 2012 University of Cambridge, Department of Engineering, Technical ...
Keck Voon Ling +3 more
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Parallelized model predictive control [PDF]
2013 American Control Conference, 2013 Model predictive control (MPC) has been used in many industrial applications because of its ability to produce optimal performance while accommodating constraints. However, its application on plants with fast time constants is difficult because of its computationally expensive algorithm. In this research, we propose a parallelized MPC that makes use of
Damoon Soudbakhsh, Anuradha M. Annaswamy
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Robustification of model predictive control [PDF]
Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 2002 A general procedure leading to an enhancement of robustness of existing model predictive control techniques is proposed. This procedure, which considers additive modeling errors, is illustrated for the case of cautious stable predictive control. The basic idea is the augmentation of the cost function with an additional term related to a description of ...
Daniel E. Quevedo, Mario E. Salgado
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Interval Model Predictive Control [PDF]
IFAC Proceedings Volumes, 2000 Model Predictive Control is one of the most popular control strategy in the process industry. One of the reason for this success can be attributed to the fact that constraints and uncertainties can be handled. There are many techniques based on interval mathematics that are used in a wide range of applications.
Burgos Bravo, José Miguel +2 more
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On output feedback nonlinear model predictive control using high gain observers for a class of systems [PDF]
, 2001 In recent years, nonlinear model predictive control schemes have been derived that guarantee stability of the closed loop under the assumption of full state information.
Imsland, L. +4 more
core +4 more sources
Recurrent Model Predictive Control
CoRR, 2021 arXiv admin note: substantial text overlap with arXiv:2102 ...
Zhengyu Liu +7 more
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CoRR, 2023 arXiv admin note: text overlap with arXiv:2104 ...
Prabhat Kumar Mishra +3 more
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