Lasso-MPC - Predictive Control with ¿1-Regularised Least Squares
Marco Gallieri
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Lasso-MPC - Predictive Control with ¿1-Regularised Least Squares

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This thesis proposes a novel Model Predictive Control (MPC) strategy, which modifies the usual MPC cost function in order to achieve a desirable sparse actuation. It features an 1-regularised least squares loss function, in which the control error variance competes with the sum of input channels magnitude (or slew rate) over the whole horizon length. While standard control techniques lead to continuous movements of all actuators, this approach enables a selected subset of actuators to be used, the others being brought into play in exceptional circumstances. The same approach can also be used t...