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SUMMARY:Model Predictive Control for changing operation conditions - Danie
 l Limon\, University of Seville
DTSTART:20160303T140000Z
DTEND:20160303T150000Z
UID:TALK63214@talks.cam.ac.uk
CONTACT:Tim Hughes
DESCRIPTION:Model predictive control (MPC) is one of the most successful a
 dvanced control technique thanks to its capability to cope with the constr
 aints of the state and inputs and to minimize the performance of the plant
 . \n\nThe MPC is typically designed to regulate the plant in a certain equ
 ilibrium point or periodic trajectory where the plant is operated. \n\nHow
 ever\,  the operation conditions of the system might be changed\, due to c
 hanges in the reference signal (in a tracking control problem)  or changes
  in the economic cost function used to calculate the optimal operation of 
 the plant (in an economic control problem).\n\nIn this scenario\, the cont
 roller must steer the system to the new equilibrium point or periodic traj
 ectory\, which may lead to possible loss of feasibility and stability of t
 he designed predictive controller.\n\nThis talk is devoted to present rece
 nt results on model predictive control techniques capable to cope with abr
 upt and random changes in the operation conditions ensuring feasibility an
 d stability to the new operation point or trajectory.
LOCATION:Cambridge University Engineering Department\, LR5
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