Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/16385
Title: Approaches to the Design of Model Predictive Controller for Constrained Linear Systems with Bounded Disturbances
Authors: WANG CHEN
Keywords: Model predictive control, constrained linear systems, stability, disturbance feedback, design of feedback gain, stochastic systems
Issue Date: 25-Nov-2009
Source: WANG CHEN (2009-11-25). Approaches to the Design of Model Predictive Controller for Constrained Linear Systems with Bounded Disturbances. ScholarBank@NUS Repository.
Abstract: This thesis is concerned with the Model Predictive Control (MPC) of linear discrete time-invariant systems with state and control constraints and subject to bounded disturbances. This thesis proves the minimal disturbance invariant set convergence under MPC controller derived using affine disturbance feedback parameterization in several ways for the first time in the literature. The second contribution of this thesis is the segregated disturbance feedback parameterization which generalizes all the previous parameterizations and preserves all the stability results. The third contribution of this thesis is a feedback gain design approach which helps to determine the feedback gain needed for the previously proposed parameterizations. Finally, MPC of systems with probabilistic constraints are considered. The concept of probabilistically constraint-admissible set is proposed and studied and applied in the design of MPC controllers.
URI: http://scholarbank.nus.edu.sg/handle/10635/16385
Appears in Collections:Ph.D Theses (Open)

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