Identification of Finite State Models of A Human Operator.
Abstract
The abstract structure of the discrete control problem as it relates to manned systems has been refined and clarified. It has been shown that input-output data (information inputs to the operator, decision outputs from him) are representable by stochastic automata, a special type of discrete parameter, discrete state stochastic process. Further, the detailed structure of these systems has been examined and it has been shown that automata based on 1th order state spaces (i.e., states are sequences of outputs) including the present and preceding 1-1 outputs) serve as excellent surogates for more general systems. The results are a set of state transition matrices and probability distributions which stochastically characterize, as a function of the input when the operator will switch the mode of operation or configuration of the system and what the new configuration will be. The results show that finite state models of the human operator performing discrete control tasks can be developed and identified from data. They further verify the feasibility of using a hierarchical structure to avoid combinatorial problems and maintain identifiability.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1977
- Accession Number
- ADA053017
Entities
People
- Ingjaldur Hannibalsson
- Richard A. Miller
- Samuel C. Mcnamee
Organizations
- Ohio State University