Distributed Optimization System
Abstract
A search system and method for controlling multiple agents to optimize an objective using distributed sensing and cooperative control. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace. The objective can be: chemical sources, temperature sources, radiation sources, light sources, evaders, trespassers, explosive sources, time dependent sources, time independent sources, function surfaces, maximization points, minimization points, and optimal control of a system such as a communication system, an economy, a crane, and a multi-processor computer.
- Inventors:
-
- Albuquerque, NM
- (Tijeras, NM)
- Issue Date:
- Research Org.:
- Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- OSTI Identifier:
- 879972
- Patent Number(s):
- 6826431
- Application Number:
- 10/392542
- Assignee:
- Sandia Corporation (Albuquerque, NM)
- Patent Classifications (CPCs):
-
G - PHYSICS G05 - CONTROLLING G05B - CONTROL OR REGULATING SYSTEMS IN GENERAL
Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y02 - TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE Y02P - CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- DOE Contract Number:
- AC04-94AL85000
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Hurtado, John E, Dohrmann, Clark R, and Robinett, III, Rush D. Distributed Optimization System. United States: N. p., 2004.
Web.
Hurtado, John E, Dohrmann, Clark R, & Robinett, III, Rush D. Distributed Optimization System. United States.
Hurtado, John E, Dohrmann, Clark R, and Robinett, III, Rush D. Tue .
"Distributed Optimization System". United States. https://www.osti.gov/servlets/purl/879972.
@article{osti_879972,
title = {Distributed Optimization System},
author = {Hurtado, John E and Dohrmann, Clark R and Robinett, III, Rush D.},
abstractNote = {A search system and method for controlling multiple agents to optimize an objective using distributed sensing and cooperative control. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace. The objective can be: chemical sources, temperature sources, radiation sources, light sources, evaders, trespassers, explosive sources, time dependent sources, time independent sources, function surfaces, maximization points, minimization points, and optimal control of a system such as a communication system, an economy, a crane, and a multi-processor computer.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Nov 30 00:00:00 EST 2004},
month = {Tue Nov 30 00:00:00 EST 2004}
}
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.
Works referenced in this record:
ALLIANCE: an architecture for fault tolerant, cooperative control of heterogeneous mobile robots
conference, January 1994
- Parker, L. E.
- Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94)
A decentralized cooperation protocol for autonomous robotic agents
conference, April 1995
- Lin, Fang-Chang; Hsu, J. Yung-Jen
- Proceedings ISADS 95. Second International Symposium on Autonomous Decentralized Systems
Cooperative search and rescue with a team of mobile robots
conference, January 1997
- Jennings, J. S.; Whelan, G.; Evans, W. F.
- 1997 8th International Conference on Advanced Robotics. Proceedings. ICAR'97
Touch Points in Optimal Ascent Trajectories with First-Order State Inequality Constraints
journal, July 1998
- Park, Sang-Young; Vadali, Srinivas R.
- Journal of Guidance, Control, and Dynamics, Vol. 21, Issue 4
A shortcoming of the multilevel optimization technique
journal, July 1971
- Avery, C. J.; Foss, A. S.
- AIChE Journal, Vol. 17, Issue 4