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Titlebook: Nonlinear Model Predictive Control; Towards New Challeng Lalo Magni,Davide Martino Raimondo,Frank Allgöwer Book 2009 Springer-Verlag Berlin

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Further Results on “Robust MPC Using Linear Matrix Inequalities” that ISS is a priori guaranteed for the closed-loop system. The method is based on the solution of a set of LMIs. An explicit relation is established between the proposed method and . control design. This relation shows that the LMI-based optimal solution of the . synthesis problem solves the termi
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LMI-Based Model Predictive Control for Linear Discrete-Time Periodic Systemsnew periodic state feedback control law is computed via a convex optimization problem that minimizes an upper bound on an infinite horizon cost function subject to state and input constraints. The performance of the proposed model predictive controller, that stabilizes the discrete-time periodic sys
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Receding Horizon Control for Linear Periodic Time-Varying Systems Subject to Input Constraintsoposed. The presented approach guarantees that input constraints are always satisfied if the optimization problem is feasible at the initial time..Unlike the usual approaches for linear systems, a finite prediction horizon is used. Stability is ensured by choosing a time-varying terminal cost, that
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Hierarchical Model Predictive Control of Wiener Modelsdel, while the systems at the lower level, which represent the fast actuators dynamics, are described by general nonlinear models. The proposed control structure guarantees steady-state zero error regulation for constant reference signals and allows one to largely decouple the control design phase a
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