Abstract
AbstractThis work considers the fast solution of model predictive control problems for linear systems with input constraints and a quadratic cost criterion. If the resulting optimization problem arising from the model predictive control is solved online using the Fast Gradient method one needs to determine the gradient of the cost function. We propose a method, tailored for embedded control purposes, that efficiently calculates the gradient taking the underlying structure of the system into account. Moreover, we discuss how the stability of the plant influences the required number of iterations to obtain a solution within a prescribed accuracy.
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