Decentralized adaptive control of large scale systems, with application to robotics

Technical Report · Tue Mar 01 04:00:00 EST 1988

OSTI ID:6832615

Gravel, Jr, D T

Present day economic, technological, and environmental systems are large and complex. Gaining an understanding of large scale systems, that is, modeling their behavior and designing appropriate stabilizing controls, is a foremost challenge of modern system theory. One approach to large scale system modeling and control is decomposition of the large system into smaller, more manageable units. This is known as the decentralized approach. Decentralized control schemes have proven to be robust to a large range of uncertainties and nonlinearities in interconnections and subsystem dynamics. For the purpose of decentralized control, decompositions of large scale systems are typically formulated to isolate uncertainty about system behavior to the interaction between subsystems. Thereby the subsystems themselves are well modeled and decentralized controllers can be designed according to standard techniques. In this thesis, the theory of decentralized adaptive control for decentrally stabilizable systems has been developed. The new schemes depend upon local high gain feedback to stabilize local systems sufficiently to overcome interconnection disturbances, leading to a stable overall system.

• Research Organization: Lawrence Livermore National Lab., CA (USA)
• DOE Contract Number: W-7405-ENG-48
• OSTI ID: 6832615
• Report Number(s): UCRL-53866; ON: DE88015409
• Country of Publication: United States
• Language: English

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FEEDBACK
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MATRICES
ROBOTS