scholarly journals Manual control behaviors in the two-axis tracking systems. Effects of the coupling factor and study of human operator models

1990 ◽  
Vol 26 (2) ◽  
pp. 59-66
Author(s):  
Tetsuro EMA
Keyword(s):  
Coupling Factor ◽  
Human Operator ◽  
Manual Control ◽  
Tracking Systems

Human Operator Decision-Making in Manual Control

1969 ◽  
Vol 10 (2) ◽  
pp. 41-47 ◽  
Author(s):  
Harry Cohen ◽  
William Ferrell
Keyword(s):  
Decision Making ◽  
Human Operator ◽  
Manual Control

A Technical Approach to Safe Mode Management for a Smooth Transition from Automatic to Manual Drilling

2021 ◽  
Author(s):  
Eric Cayeux ◽  
Rodica Mihai ◽  
Liv Carlsen ◽  
Morten Ørevik ◽  
Kjartan Birgisson ◽  
...  
Keyword(s):  
Transition State ◽  
Situation Awareness ◽  
Smooth Transition ◽  
Human Operator ◽  
Manual Control ◽  
Construction Operations ◽  
System Failures ◽  
Autonomous Function ◽  
Current State ◽  
The One

Abstract Unexpected situations and system failures during well construction operations are always possible. In the context of drilling automation, or even autonomous drilling, proper automatic management of these situations is of critical importance as the situation awareness of the human operator is very much reduced. The proper management of the transition between automatic and manual modes is necessary to improve the safety of automation solutions. An important characteristic of drilling automation solutions is their ability to cope with unexpected situations. This also encompasses, placing the drilling system in a state that is easy and intuitive for the human operator when manual control is required. Our approach to safe mode management is dependent on a good state estimation of the current conditions of the process. If for any reason, manual control must be regained, then the automated function itself triggers the necessary actions that will ensure a stable current state. In case of a drilling problem or a system failure, the human operator may have to regain control when the context might be totally different from the one left when the automation or autonomous function was enabled. It may even be a different human operator that has to take control, if a crew change has taken place. To make the transition from the automated/autonomous context to manual control, the automation/autonomous system sets the drilling machines in a so-called safe transition state. A safe transition state is one for which leaving the current setpoints of drilling machines untouched for a reasonable amount of time, will not immediately jeopardize the safety of the drilling operation. A safe transition state is contextual as it is not necessarily the same sequence of actions that must be performed to reach the safe transition state every time. The novel safe modes management method is integrated into existing drilling automation solutions. In a drilling automation context, the situation awareness of the human operator is considerably reduced as the automated functions control the process and the human operator is not actively driving the drilling machines. Without active safe mode management, there is a risk that drilling automation solutions may lead to serious situations as the driller may be totally unprepared to regain control in the middle of a critical situation. When it is needed to return to manual mode in the middle of the execution of an automatic procedure, an adequate procedure is executed. The choice of the procedure and its parameters depend on the current state of the process and system.

Nonlinear and Time-Varying Dynamical Models of Human Operators in Manual Control Systems

1966 ◽  
Vol 8 (2) ◽  
pp. 97-120 ◽  
Author(s):  
Walter W. Wierwille ◽  
Gilbert A. Gagne
Keyword(s):  
Control System ◽  
Linear Time ◽  
Human Operator ◽  
Manual Control ◽  
Time Variability ◽  
Time Varying ◽  
Deterministic Theory ◽  
Manual Control System ◽  
New Information ◽  
Human Operators

This paper describes the application of a deterministic theory for characterizing or modeling the dynamics of a human operator in a manual control system. Linear time-varying, nonlinear time-varying, and non-linear constant-coefficient models are obtained by applying the theory to tracking data taken for one- and two-axis tasks with various displays. The accuracy and fidelity of these advanced models are explored in detail. Also, new information about time variability and nonlinearity of the human operator, obtained by studying the models and the manual control system signals, is presented.

Detecting Slow Changes in System Dynamics

1974 ◽  
Vol 16 (3) ◽  
pp. 278-285 ◽  
Author(s):  
Fuat Ince ◽  
Robert C. Williges
Keyword(s):  
System Dynamics ◽  
Adaptive Behavior ◽  
Laboratory Experiments ◽  
Rate Of Change ◽  
Tracking Performance ◽  
Human Operator ◽  
Manual Control ◽  
Sufficient Time ◽  
Standard Level

Two laboratory experiments were performed to study the human operator's adaptive behavior in manual control of slowly changing system dynamics. In the first experiment, the dynamics changed from rate to acceleration control. In the second experiment, the control stick sensitivity slowly increased or slowly decreased from a standard level. Tracking performance on a compensatory task demonstrated that the human operator lags in adapting to the changing system dynamics, but he does adapt when given sufficient time. As the rate of change increases, the human operator needs a larger change for detection of the change and less time to detect the changing system dynamics.

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