Case Study #2: Collective Systems and Controls

  • Rush D. RobinettIII
  • David G. Wilson
Part of the Understanding Complex Systems book series (UCS)


The goal of Chap. 7 is to design and analyze distributed decentralized control laws for a team of robots performing collective plume tracing based on HSSPFC and information theory. Chapter 7 begins with a discussion of the fundamental importance of the Hamiltonian function and the application of equilibrium thermodynamics to bound the problem. The design and analysis process continues with the design of a kinematic controller based on the application of HSSPFC. The resulting kinematic controller is evaluated based on Shannon information theory and a fundamental trade-off between processing, memory, and communications. The process is completed with the design of a kinetic controller based on Hamiltonian surface shaping with physical and information exergies in the form of control potentials that determine the accessible phase space of the power flow controller. The resulting kinetic controller is evaluated using Fisher Information which leads to a Fisher Information Equivalency (FIE). The FIE can be used to optimize as well as trade-off between the physical energy storage and information resources required to accomplish the operation while meeting the necessary and sufficient conditions for stability of a class of nonlinear systems.


Fisher Information Collective System Model Predictive Control Search Volume Robot Swarm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Sandia National LaboratoriesAlbuquerqueUSA

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