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Model predictive control based on adaptive hinging hyperplanes model
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AI
DOI：10.1016/j.jprocont.2012.10.007.png)
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The model of adaptive hinging hyperplanes (AHH) is used in model predictive control (MPC). The nonlinear dynamic system is approximated by the continuous piecewise affine (CPWA) model AHH and the controller design problem becomes a continuous piecewise quadratic programming. The necessary and sufficient conditions for a point to be locally optimal for such a problem are established, based on which, a descent algorithm is developed to find a local optimum. Issues concerning feasibility and stability are also discussed. Simulations are conducted to confirm the effectiveness of the proposed MPC strategy. (C) 2012 Elsevier Ltd. All rights reserved.
Keyword:
Model predictive control
Adaptive hinging hyperplanes
Piecewise affine
Local optimum
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3.9
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3.5K
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