The Internal Model Concept: An Application to Modeling Human Control of Large Ships

Author(s):  
Wim Veldhuyzen ◽  
Henk G. Stassen

Many human operator studies have used successfully the concept that the human operator performs his task on the basis of certain knowledge about the system to be controlled, called the internal model. In this paper, the literature on manual control will be reviewed briefly with attention focused on the use of the internal model concept. To illustrate the applicability of the internal model concept in the field of man-machine systems, an application is given in the human control of large ships. A model to describe the helmsman's behavior in steering a supertanker, and the influence on his behavior of additional displays such as a rate of turn indicator will be described.

1969 ◽  
Vol 10 (2) ◽  
pp. 41-47 ◽  
Author(s):  
Harry Cohen ◽  
William Ferrell

2021 ◽  
Author(s):  
Eric Cayeux ◽  
Rodica Mihai ◽  
Liv Carlsen ◽  
Morten Ørevik ◽  
Kjartan Birgisson ◽  
...  

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.


2019 ◽  
Vol 135 ◽  
pp. 01006 ◽  
Author(s):  
Alexandr Saushev ◽  
Vladimir Tyrva ◽  
Lev Kovtun

The problem of implementing joint control actions on electromechanical devices (EMD) in human-machine systems through the control body of a human-machine interface is considered. Based on the theory of optimal control, control functions between the human operator, the program control automaton, and the corrective control automaton are synthesized. Peculiarities of the technical implementation of the control actions on the EMD of the ergatic system using the new type of joint control devices have been identified, through the control body of which information interaction between the human operator and the system automa-ton is carried out. Based on the model of actions and responses of the human operator and machine, which is adopted in engineering psychology, mathematical models of their joint control of the object have been developed. Mathematical models of machine responses are constructed using the hypothesis of complete certainty in the form of a normal system of ordinary differen-tial equations. As a result of combining action and response models for the human-machine system, a finite set of incomplete representations of the elementary motions of the image point in the state space is obtained, on which the programmed motion of the object is built in the form of a sequence of elementary motions. Virtual discrete control signals Corresponding to specific positions of the control bodies of the joint control apparatuses of the human-machine interface of the system are determined, through which consecutive transitions from one elementary movement to another are carried out. The conclusions on the effectiveness of the use of joint control in transport ergatic human-machine systems are formulated. It is shown that in this case, the advantages of control partners are used and combined to the greatest extent.


Author(s):  
Walter W. Wierwille ◽  
Gilbert A. Gagne

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.


Author(s):  
Richard J. Jagacinski ◽  
Richard A. Miller

An analysis of phase-plane switching loci was used to infer the human operator's internal model of a dynamic system he was attempting to control. Striking differences were found between the internal model and the actual dynamic system, and the internal model exhibited orderly changes with practice. The difficulties involved in incorporating a non-veridical internal model into optimal control models of the human operator are discussed.


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