Discrete-Time Linear Model Predictive Control
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Date
2016-07-04
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Addis Ababa University
Abstract
Model predictive control is a form of control in which the current control action is obtained
by solving on-line, at each sampling instant, a _nite horizon optimal control problem, using
the current state of the plant as the initial state; the optimization yields an optimal control
sequence and the _rst control in this sequence is applied to the plant. An important
advantage of this type of control is its ability to cope with hard constraints on controls and
states. In this project, we discuss model predictive control(MPC) schemes for discrete-time
linear time-invariant state space system with and without constraints on inputs, states and
outputs. The constraints on inputs, states and outputs are in the form of bounds, that can
be formulated as linear inequalities. In particular, the project focus on performance criteria
based on quadratic form. And also, discuss some solution techniques of discrete-time model
predictive control using quadratic programming solution techniques.
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Discrete-Time Linear