BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Fault-Tolerant Predictive Control: A Gaussian Process Model Based 
 Approach - Xiaoke Yang\, University of Cambridge
DTSTART:20141030T140000Z
DTEND:20141030T150000Z
UID:TALK55748@talks.cam.ac.uk
CONTACT:Tim Hughes
DESCRIPTION:Essential ingredients for fault-tolerant control are the abili
 ty to represent system behaviour following the occurrence of a fault\, and
  the ability to exploit this representation for deciding control actions. 
 In this talk\, we discuss a fault-tolerant control approach based on a mod
 el predictive control (MPC) framework with a probabilistic model\, namely 
 a Gaussian process (GP)\, with the aim of more flexible identification and
  effective control under fault conditions (possibly unexpected ones). This
  approach is characterised by a probabilistic representation of the system
 \, the online learning to update the representation from input-output data
 \, and the optimisation over this up-to-date model in a predictive control
 ler for an enhanced control action. \n\nSuch a control framework is implem
 ented and its fault-tolerant capability is investigated. Through computer 
 simulations\, the GP model in the MPC is demonstrated to be able to captur
 e various fault conditions that change the system's input-to-state behavio
 ur and the system's dynamic behaviour. Given the updated GP model\, the MP
 C is also shown to be effective in the fault scenarios investigated. Addit
 ionally\, control actions under cost functions with different probabilisti
 c cost over states demonstrate the cautious control action from an expecte
 d-quadratic cost\, as well as the effective exploratory actions from a ris
 k-seeking cost. The effectiveness of the said framework is further evaluat
 ed on a high-fidelity flight control benchmark\, the GARTEUR RECOVER bench
 mark. Both longitudinal control and full-state control demonstrate the con
 troller's capability to tolerate actuator faults like 'stuck-in-position' 
 and 'runaway'.
LOCATION:Cambridge University Engineering Department\, LR5
END:VEVENT
END:VCALENDAR