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...

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Detaylı Bibliyografya
Yazar: Gallieri, Marco (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edisyon:1st ed. 2016.
Seri Bilgileri:Springer Theses, Recognizing Outstanding Ph.D. Research,
Konular:
Control engineering.
System theory.
Control theory.
Computer simulation.
Control and Systems Theory.
Systems Theory, Control.
Computer Modelling.
Online Erişim:Full-text access
OPAC'ta görüntüle
İçindekiler:
  • 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.

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