scholarly journals Memory Pattern Identification for Feedback Tracking Control in Human–Machine Systems

2019 ◽  
pp. 001872081988100 ◽  
Author(s):  
Miguel Martínez-García ◽  
Yu Zhang ◽  
Timothy Gordon
Keyword(s):  
Fractional Order ◽  
Finite Impulse Response ◽  
Human Subjects ◽  
Procedural Memory ◽  
Human Operator ◽  
Human Model ◽  
Manual Control ◽  
Control Task ◽  
Fir Model ◽  
Memory Pattern

Objective: The aim of this paper was to identify the characteristics of memory patterns with respect to a visual input, perceived by the human operator during a manual control task, which consisted in following a moving target on a display with a cursor. Background: Manual control tasks involve nondeclarative memory. The memory encodings of different motor skills have been referred to as procedural memories. The procedural memories have a pattern, which this paper sought to identify for the particular case of a one-dimensional tracking task. Specifically, data recorded from human subjects controlling dynamic systems with different fractional order were investigated. Method: A finite impulse response (FIR) controller was fitted to the data, and pattern analysis of the fitted parameters was performed. Then, the FIR model was further reduced to a lower order controller; from the simplified model, the stability analysis of the human–machine system in closed-loop was conducted. Results: It is shown that the FIR model can be used to identify and represent patterns in human procedural memories during manual control tasks. The obtained procedural memory pattern presents a time scale of about 650 ms before decay. Furthermore, the fitted controller is stable for systems with fractional order less than or equal to 1. Conclusion: For systems of different fractional order, the proposed control scheme—based on an FIR model—can effectively characterize the linear properties of manual control in humans. Application: This research supports a biofidelic approach to human manual control modeling over feedback visual perceptions. Relevant applications of this research are the following: the development of shared-control systems, where a virtual human model assists the human during a control task, and human operator state monitoring.

An Optimization Model of Self-Paced Tracking

1984 ◽  
Vol 28 (4) ◽  
pp. 398-402
Author(s):  
M. A. Montazer ◽  
Colin G. Drury
Keyword(s):  
Human Performance ◽  
Human Subjects ◽  
Line Drawing ◽  
Manual Control ◽  
Sampled Data ◽  
Control Task ◽  
Drawing Task ◽  
Model Predictions ◽  
Human Operators ◽  
Fixed Boundaries

A model which describes human performance in a self-paced tracking task was developed based on the notion that human operators are intermittent-acting or sampled-data servo-mechanisms. The model had a functional form in terms of the probability of success and failure resulting from the execution of a manual control task such as drawing a line between fixed boundaries. The human operator was modelled as an optimizer, balancing costs and penalties of speeds and errors to achieve a maximum expected payoff. The performance of the model was evaluated by simulating a line drawing task on a digital computer. Model predictions obtained via simulation were compared with the data collected from human subjects performing the actual task in a laboratory setting. The predictions of the model were confirmed, suggesting that human operators can in fact be modelled as optimizers when performing a manual control task.

Data-to-sound mapping to sonify ongoing system status in continuous manual control task

2011 ◽  
Author(s):  
Yukio Horiguchi ◽  
Keisuke Yasuda ◽  
Hiroaki Nakanishi ◽  
Tetsuo Sawaragi
Keyword(s):  
Manual Control ◽  
Control Task

scholarly journals Grasping Assisting Algorithm in Tele-Operated Robotic Gripper

2021 ◽  
Vol 11 (6) ◽  
pp. 2640
Author(s):  
Tomer Fine ◽  
Guy Zaidner ◽  
Amir Shapiro
Keyword(s):  
State Of The Art ◽  
Human Subjects ◽  
Quality Measures ◽  
Human Operator ◽  
Physical Presence ◽  
Complete State ◽  
The Future ◽  
Power Grasp ◽  
Grasp Quality

The involvement of Robots and automated machines in different industries has increased drastically in recent years. Part of this revolution is accomplishing tasks previously performed by humans with advanced robots, which would replace the entire human workforce in the future. In some industries the workers are required to complete different operations in hazardous or difficult environments. Operations like these could be replaced with the use of tele-operated systems that have the capability of grasping objects in their surroundings, thus abandoning the need for the physical presence of the human operator at the area while still allowing control. In this research our goal is to create an assisting system that would improve the grasping of a human operator using a tele-operated robotic gripper and arm, while advising the operator but not forcing a solution. For a given set of objects we computed the optimal grasp to be achieved by the gripper, based on two grasp quality measures of our choosing (namely power grasp and precision grasp). We then tested the performance of different human subjects who tried to grasp the different objects with the tele-operated system, while comparing their success to unassisted and assisted grasping. Our goal is to create an assisting algorithm that would compute optimal grasps and might be integrated into a complete, state-of-the-art tele-operated system.

scholarly journals Human manual control precision depends on vestibular sensory precision and gravitational magnitude

2018 ◽  
Vol 120 (6) ◽  
pp. 3187-3197 ◽  
Author(s):  
Marissa J. Rosenberg ◽  
Raquel C. Galvan-Garza ◽  
Torin K. Clark ◽  
David P. Sherwood ◽  
Laurence R. Young ◽  
...  
Keyword(s):  
Manual Control ◽  
Control Performance ◽  
Control Task ◽  
Altered Gravity ◽  
Control Precision ◽  
Functional Implications ◽  
Potential Risk Factors ◽  
And Performance ◽  
Human Exploration ◽  
Roll Tilt

Precise motion control is critical to human survival on Earth and in space. Motion sensation is inherently imprecise, and the functional implications of this imprecision are not well understood. We studied a “vestibular” manual control task in which subjects attempted to keep themselves upright with a rotational hand controller (i.e., joystick) to null out pseudorandom, roll-tilt motion disturbances of their chair in the dark. Our first objective was to study the relationship between intersubject differences in manual control performance and sensory precision, determined by measuring vestibular perceptual thresholds. Our second objective was to examine the influence of altered gravity on manual control performance. Subjects performed the manual control task while supine during short-radius centrifugation, with roll tilts occurring relative to centripetal accelerations of 0.5, 1.0, and 1.33 GC (1 GC = 9.81 m/s2). Roll-tilt vestibular precision was quantified with roll-tilt vestibular direction-recognition perceptual thresholds, the minimum movement that one can reliably distinguish as leftward vs. rightward. A significant intersubject correlation was found between manual control performance (defined as the standard deviation of chair tilt) and thresholds, consistent with sensory imprecision negatively affecting functional precision. Furthermore, compared with 1.0 GC manual control was more precise in 1.33 GC (−18.3%, P = 0.005) and less precise in 0.5 GC (+39.6%, P < 0.001). The decrement in manual control performance observed in 0.5 GC and in subjects with high thresholds suggests potential risk factors for piloting and locomotion, both on Earth and during human exploration missions to the moon (0.16 G) and Mars (0.38 G). NEW & NOTEWORTHY The functional implications of imprecise motion sensation are not well understood. We found a significant correlation between subjects’ vestibular perceptual thresholds and performance in a manual control task (using a joystick to keep their chair upright), consistent with sensory imprecision negatively affecting functional precision. Furthermore, using an altered-gravity centrifuge configuration, we found that manual control precision was improved in “hypergravity” and degraded in “hypogravity.” These results have potential relevance for postural control, aviation, and spaceflight.

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

Control valve stiction compensation by dynamic inversion: a comparative study

2018 ◽  
Vol 24 (3) ◽  
pp. 400-419 ◽  
Author(s):  
Sami Elferik ◽  
Mohammed Hassan ◽  
Mustafa AL-Naser
Keyword(s):  
Finite Impulse Response ◽  
Residual Life ◽  
Control Valve ◽  
Inverse Model ◽  
Optimization Techniques ◽  
Dynamic Inversion ◽  
Control Effort ◽  
Content Type ◽  
Valve Stiction ◽  
Fir Model

Purpose The purpose of this paper is to improve the performance of control loop suffering from control valve stiction. Control valve stiction is considered as of one of the main causes of oscillation in process variables, which require performing costly unplanned maintenance and process shutdown. An adaptive solution to handle valve stiction while maintaining safety and quality until next planned maintenance is highly desirable to save considerable cost and effort. Design/methodology/approach This paper implements a new stiction compensation method built using adaptive inverse model techniques and intelligent control theories. Finite impulse response (FIR) model, which is known to be robust, as a compensator for stiction. The parameters of FIR model are tuned in an adaptive way using differential evolution (DE) technique. The performance of proposed method is compared with other two compensation techniques. Findings The new method showed excellent performance of the DE–FIR compensator compared to other dynamic inversion methods in terms of minimizing process variability, energy saving and valve stem aggressiveness. Research limitations/implications The compensation ability for all compensators reduces with the increase of stiction severity, thus the over shoot case always shows the worst result. In future works, other optimization techniques will be explored to find the appropriate technique that can extend the FIR model size with smallest computation time that can improve the performance of the compensator in over shoot case. In addition, the estimation of the valve residual life based on the level of stiction and effort required by the controller should be considered. Originality/value The presented approach represents an original contribution to the literature. It performs stiction compensation without a need for a prior knowledge on the process or the valve models and guarantees a smooth control of the stem movement with a low control effort. The proposed approach differs from previous adaptive methods as it uses stable FIR models and DE to find the appropriate parameters of the inverse model and handle nonlinear behavior of stiction.

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.

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