ROBUST MODEL PREDICTIVE CONTROL FOR INPUT SATURATED AND SOFTENED STATE CONSTRAINTS
β Scribed by Vu Trieu Minh; Nitin Afzulpurkar
- Book ID
- 114944782
- Publisher
- John Wiley and Sons
- Year
- 2008
- Tongue
- English
- Weight
- 133 KB
- Volume
- 7
- Category
- Article
- ISSN
- 1561-8625
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## Abstract In practice, model predictive control (MPC) algorithms are typically embedded within a multilevel hierarchy of control functions. The MPC algorithm itself is usually implemented in two pieces: a steadyβstate target calculation followed by a dynamic optimization. A new formulation of the
Over The Past Few Years Significant Progress Has Been Achieved In The Field Of Nonlinear Model Predictive Control (nmpc), Also Referred To As Receding Horizon Control Or Moving Horizon Control. More Than 250 Papers Have Been Published In 2006 In Isi Journals. With This Book We Want To Bring Together
A receding horizon predictive control method which assures stability for systems with model uncertainty and input saturation is derived by extending earlier work in two important respects: (i) ellipsoidal invariant sets are replaced by polyhedral invariant sets; and (ii) the constraint that the stat