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READING ON THE GO AT UNION STATION LENDING LIBRARY
In the spring of 2015, The Union Station Redevelopment Corporation launched a […]
Y. H. Kim
Young Ho Kim
F. L. Lewis
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Orca Knowledge Systems, Inc
This book bridges the gap between feedback control and AI. It provides design techniques for "high-level" neural-network feedback-control topologies that contain servo-level feedback-control loops as well as AI decision and training at the higher levels. Several advanced feedback topologies containing neural networks are presented, including "dynamic output feedback", "reinforcement learning" and "optimal design", as well as a "fuzzy-logic reinforcement" controller. The control topologies are intuitive, yet are derived using sound mathematical principles where proofs of stability are given so that closed-loop performance can be relied upon in using these control systems. Computer-simulation examples are given to illustrate the performance.
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