Lasso-MPC – Predictive Control with ℓ1-Regularised Least Squares

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 ℓ1-regularised least squares loss function, in which the control error variance competes with the sum of input channels ma...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Gallieri, Marco (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
Σειρά:Springer Theses, Recognizing Outstanding Ph.D. Research,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Introduction
  • Background
  • Principles of LASSO MPC
  • Version 1: `1-Input Regularised Quadratic MPC.-  Version 2: LASSO MPC with stabilising terminal cost
  • Design of LASSO MPC for prioritised and auxiliary actuators
  • Robust Tracking with Soft-constraints
  • Ship roll reduction with rudder and fins
  • Concluding Remarks.