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Quantized nonlinear model predictive control for a building
2015 IEEE Conference on Control Applications (CCA), 2015In this paper, the task of quantized nonlinear predictive control is addressed. In such case, values of some inputs can be from a continuous interval while for the others, it is required that the optimized values belong to a countable set of discrete values.
Matej Pcolka +4 more
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Robust Model Predictive Control for Nonlinear Systems
2011On the basis of the fuzzy T-S (Takagi-Sugeno) model, we propose a robust model predictive control for a class of nonlinear systems with constraint inputs. The upper bound of predictive cost is derived; the constraints on stability and inputs are transformed into linear matrix inequalities (LMIs), which can be easily solved.
Yang Li, Yuanying Qiu, Jun Zhang
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Special section on Nonlinear Model Predictive Control
Annual Reviews in Control, 2016Reference EPFL-ARTICLE-221985doi:10.1016/j.arcontrol.2016.04.007View record in Web of Science Record created on 2016-10-18, modified on 2016-10 ...
Daniel Limón +2 more
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Nonlinear Model Predictive Path-Following Control
2009In the frame of this work, the problem of following parametrized reference paths via nonlinear model predictive control is considered. It is shown how the use of parametrized paths introduces new degrees of freedom into the controller design. Sufficient stability conditions for the proposed model predictive path-following control are presented.
Faulwasser, T., Findeisen, R.
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Nonlinear Model Predictive Control with Latent Force Models
2022 American Control Conference (ACC), 2022Daniel Landgraf +2 more
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Considerations on nonlinear model predictive control techniques
Computers & Chemical Engineering, 2011Abstract The nonlinear model predictive control (NMPC) is an on-line application based on nonlinear convolution models. It is an appealing control methodology, but it is difficult to implement and its solution is not so performing since it unavoidably means to solve a usually large-scale, constrained, and multidimensional optimization.
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Computationally Efficient Nonlinear Model Predictive Control
2022 8th International Conference on Control, Decision and Information Technologies (CoDIT), 2022Zhijia Yang +4 more
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An Efficient Accelerator for Nonlinear Model Predictive Control
2023 IEEE 34th International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2023Sergio A. Pertuz 0001 +2 more
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Offset-Free Nonlinear Model Predictive Control
2017Offset-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. A brief formulation of the MPC formulation used is first given, followed by a brief remainder of the case with measured state vector.
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