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SUMMARY:Decentralized Optimal Control and Connections to the Human Motor S
 ystem - Dr Andrew Lamperski\, California Institute of Technology
DTSTART:20120302T140000Z
DTEND:20120302T150000Z
UID:TALK36610@talks.cam.ac.uk
CONTACT:Rachel Fogg
DESCRIPTION:Optimal control theory has become a dominant mathematical fram
 ework for studying human movement\, but major gaps remain in the understan
 ding of how such control schemes are implemented in neural hardware. In pa
 rticular\, most of modern control theory assumes that control laws are imp
 lemented using a perfect\, centralized\, and infinitely fast computer. In 
 contrast\, a human must implement control using a distributed network of s
 low\, noisy neurons. Motivated by the presence of delays in the human moto
 r system\, I will discuss the architecture of optimal decentralized contro
 llers when communication between subsystems is limited by delays. I will p
 resent state feedback and output feedback control schemes that are\, to my
  knowledge\, the first known explicit solutions to some classical  problem
 s in decentralized control. In the case of decentralized state feedback\, 
 the structure that emerges as the result of optimization resembles a manag
 ement hierarchy. When output feedback is considered\, however\, the hierar
 chical structure is less apparent. Throughout the talk\, I will attempt to
  relate the architectural results to the organization of the motor system.
LOCATION:Cambridge University Engineering Department\, LR6
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