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000754499 020__ $$a9783319279633$$q(electronic book)
000754499 020__ $$a3319279637$$q(electronic book)
000754499 020__ $$z9783319279619
000754499 0247_ $$a10.1007/978-3-319-27963-3$$2doi
000754499 035__ $$aSP(OCoLC)ocn945771678
000754499 035__ $$aSP(OCoLC)945771678
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000754499 049__ $$aISEA
000754499 050_4 $$aTJ217.6
000754499 08204 $$a629.8$$223
000754499 1001_ $$aGallieri, M.$$q(Marco),$$d1985-$$eauthor.
000754499 24510 $$aLasso-MPC -- predictive control with L1-regularised least squares$$h[electronic resource] /$$cMarco Galleri.
000754499 264_1 $$aSwitzerland :$$bSpringer,$$c2016.
000754499 300__ $$a1 online resource (xxx, 187 pages) :$$billustrations.
000754499 336__ $$atext$$btxt$$2rdacontent
000754499 337__ $$acomputer$$bc$$2rdamedia
000754499 338__ $$aonline resource$$bcr$$2rdacarrier
000754499 4901_ $$aSpringer theses
000754499 500__ $$a"Doctoral thesis accepted by the University of Cambridge, UK."
000754499 504__ $$aIncludes bibliographical references.
000754499 5050_ $$aIntroduction -- 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.
000754499 506__ $$aAccess limited to authorized users.
000754499 520__ $$aThis 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 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 to obtain asynchronous actuator interventions, so that control actions are only taken in response to large disturbances. This thesis presents a straightforward and systematic approach to achieving these practical properties, which are ignored by mainstream control theory.
000754499 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed April 7, 2016).
000754499 650_0 $$aPredictive control.
000754499 650_0 $$aLeast squares.
000754499 77608 $$iPrint version:$$z9783319279619
000754499 830_0 $$aSpringer theses.
000754499 852__ $$bebk
000754499 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-27963-3$$zOnline Access$$91397441.1
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