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...
Κύριος συγγραφέας: | |
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Συγγραφή απο Οργανισμό/Αρχή: | |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2016.
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Σειρά: | Springer Theses, Recognizing Outstanding Ph.D. Research,
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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.