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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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Gallieri, Marco (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:Inglés
Published: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edition:1st ed. 2016.
Series:Springer Theses, Recognizing Outstanding Ph.D. Research,
Subjects:
Control engineering.
System theory.
Control theory.
Computer simulation.
Control and Systems Theory.
Systems Theory, Control .
Computer Modelling.
Online Access:Texto Completo
Table of Contents:
  • 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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