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Award Abstract #1330081

CPS: Synergy: Collaborative Research: Event-Based Information Acquisition, Learning, and Control in High-Dimensional Cyber-Physical Systems

NSF Org: CNS
Division Of Computer and Network Systems
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Initial Amendment Date: September 17, 2013
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Latest Amendment Date: September 17, 2013
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Award Number: 1330081
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Award Instrument: Standard Grant
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Program Manager: Radhakisan S. Baheti
CNS Division Of Computer and Network Systems
CSE Direct For Computer & Info Scie & Enginr
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Start Date: October 1, 2013
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End Date: September 30, 2016 (Estimated)
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Awarded Amount to Date: $333,334.00
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Investigator(s): Andrea Goldsmith andrea@ee.stanford.edu (Principal Investigator)
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Sponsor: Stanford University
3160 Porter Drive
Palo Alto, CA 94304-1212 (650)723-2300
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NSF Program(s): CYBER-PHYSICAL SYSTEMS (CPS)
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Program Reference Code(s): 7918
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Program Element Code(s): 7918

ABSTRACT

This project focuses on the problem of information acquisition, state estimation and control in the context of cyber physical systems. In our underlying model, a (set of) decision maker(s), by controlling a sequence of actions with uncertain outcomes, dynamically refines the belief about stochastically time-varying parameters of interest. These parameters are then used to control the physical system efficiently and robustly. Here the cyber system collects, processes, and acquires information about the underlying physical system of interest, which is used for its control. The proposed work will develop a new theoretical framework for stochastic learning, decision-making, and control in stochastically-varying cyber physical systems.

In order to obtain analytical insights into the structure of efficient design, we first consider the case where the actions of the cyber system only affect the estimate of the underlying physical system. This class of problems arises in the context of (distributed) sensing/tracking of a physical system in isolation from cyber system control of the physical system's state. Joint state estimation and control for cyber-physical systems will then be considered. Here the most natural first step is to obtain sufficient conditions and/or special classes of systems where a separated approach to the information acquisition and efficient control is (near) optimal. To demonstrate its utility in practice, our theoretical framework will be applied in the specific context of energy efficient control of data centers and robust control of the smart grid under limited sensing.

The intellectual merit of this work will be to develop a theoretical framework for the design of cyber-physical systems including information acquisition, state estimation, and control. In addition, separation theorems for the optimality of separate state estimation and control will be explored.

In terms of broader impacts, significant performance improvement of control systems closed over communication networks will impact a wide range of applications for societal benefit, including smart buildings, intelligent transportation systems, energy-efficient data centers, and the future smart-grid. The PIs plan to disseminate the research results widely through conferences and journals, as well as by organizing specialized workshops and conference sessions related to cyber physical systems. The proposed project will train Ph.D. students as well as enrich the curriculum taught by the PIs in communications, stochastic control, and networks. The PIs have a strong track record in diversity and outreach activities, which for this project will include exposure and involvement of high school and undergraduate students, including under-represented minorities and women.

 

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