Discrete-time Linear Model Predictive Control

Model predictive control is a form of control in which the current control action is obtainedrnby solving on-line, at each sampling instant, a _nite horizon optimal control problem, usingrnthe current state of the plant as the initial state; the optimization yields an optimal controlrnsequence and the _rst control in this sequence is applied to the plant. An importantrnadvantage of this type of control is its ability to cope with hard constraints on controls andrnstates. In this project, we discuss model predictive control(MPC) schemes for discrete-timernlinear time-invariant state space system with and without constraints on inputs, states andrnoutputs. The constraints on inputs, states and outputs are in the form of bounds, that canrnbe formulated as linear inequalities. In particular, the project focus on performance criteriarnbased on quadratic form. And also, discuss some solution techniques of discrete-time modelrnpredictive control using quadratic programming solution techniques.

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