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Reliability analysis in intelligent machinesGiven an explicit task to be executed, an intelligent machine must be able to find the probability of success, or reliability, of alternative control and sensing strategies. By using concepts for information theory and reliability theory, new techniques for finding the reliability corresponding to alternative subsets of control and sensing strategies are proposed such that a desired set of specifications can be satisfied. The analysis is straightforward, provided that a set of Gaussian random state variables is available. An example problem illustrates the technique, and general reliability results are presented for visual servoing with a computed torque-control algorithm. Moreover, the example illustrates the principle of increasing precision with decreasing intelligence at the execution level of an intelligent machine.
Document ID
19900064100
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Mcinroy, John E. (Rensselaer Polytechnic Inst. Troy, NY, United States)
Saridis, George N. (Rensselaer Polytechnic Institute, Troy, NY, United States)
Date Acquired
August 14, 2013
Publication Date
August 1, 1990
Publication Information
Publication: IEEE Transactions on Systems, Man, and Cybernetics
Volume: 20
ISSN: 0018-9472
Subject Category
CYBERNETICS
Funding Number(s)
CONTRACT_GRANT: NGT-50357
CONTRACT_GRANT: NAGW-1333
Distribution Limits
Public
Copyright
Other