Human Operator Dynamics Research Articles

Application of Optimization Method for Identifying Human Operator Model Parameters

The development of automation technologies in various fields of human life poses the problem of studying human-machine systems interaction and the influence of human on machine actions. The varied human behavior and the complexity of his central nervous system organization are a disability to his mathematical description. However, despite this, the human operator has efficient properties of trainability, adaptation to task variables, and optimization of system parameters. These properties allow researchers to introduce various assumptions in modeling and use them to identify the human model parameters. The purpose of this paper is to propose an approach to human operator model parameters identification by systems optimization methods. The paper is aimed to obtain a model of the human operator, which acts as a closed-loop feedback controller. The human operator model is taken in the form of the delayed lead-lag filter. Based on the assumption that the human operator optimizes system quality index, employing the optimization procedure to obtain/identify the human operator dynamics. The controlled plant model is assumed to be known and its parameters are fixed. The paper presents the results of the optimization-based identification procedure where the McRuer model in the compensatory control system was used. The proposed algorithm for calculation of the cost function is described mathematically and presented in pseudocode. Its reliability is demonstrated by comparing the numerical values of the human operator model parameters with the experimental results given in the literature.

Динамический стенд для оценки затрат времени на формы мышления человека-оператора

The paper considers design features and functionality of the dynamic stand for assessing the time spent on human operator thinking forms during the hidden (latent) period as information passes through the brain according to experimental data working in Man-Machine Systems. This research is of interest as such a system is intellectual, so it is necessary to determine the pure delay time spent to implement thinking forms for assessing the quality of decisions made by a human operator in the control process. The study shows that a number of Wiener orthogonal G-functionals provides the most complete and rigorous human operator dynamics description and mathematical capabilities for calculating the necessary delay time.

Adaptive Admittance Control for Human–Robot Interaction Using Model Reference Design and Adaptive Inverse Filtering

Corobotics involves humans and robots working collaboratively as a team. This requires physical human-robot interaction (pHRI) systems that can adapt to the preferences of different humans and have good robustness and stability properties. In this brief, a new inner-loop/outer-loop robot controller formulation is developed that makes pHRI robust to changes in both corobot and human user. First, an inner-loop controller with guaranteed robustness and stability causes a robot to behave like a prescribed admittance model. Second, an outer-loop controller tunes the admittance model so that the robot system assists humans with varying levels of skill to achieve task-specific objectives. This design technique cleanly separates robot-specific control from task performance objectives and allows formal inclusion in an outer design of both an ideal task model and unknown human operator dynamics. Experimental results with the controllers running on a PR2 robot demonstrate the effectiveness of this approach.

Fractional order modeling of human operator behavior with second order controlled plant and experiment research

Modeling human operator's dynamics plays a very important role in the manual closed-loop control system, and it is an active research area for several decades. Based on the characteristics of human brain and behavior, a new kind of fractional order mathematical model for human operator in single-input single-output (SISO) systems is proposed. Compared with the traditional models based on the commonly used quasilinear transfer function method or the optimal control theory method, the proposed fractional order model has simpler structure with only few parameters, and each parameter has explicit physical meanings. The actual data and experiment results with the second-order controlled plant illustrate the effectiveness of the proposed method.

Model reference adaptive impedance control for physical human-robot interaction

This paper presents a novel enhanced human-robot interaction system based on model reference adaptive control. The presented method delivers guaranteed stability and task performance and has two control loops. A robot-specific inner loop, which is a neuroadaptive controller, learns the robot dynamics online and makes the robot respond like a prescribed impedance model. This loop uses no task information, including no prescribed trajectory. A task-specific outer loop takes into account the human operator dynamics and adapts the prescribed robot impedance model so that the combined human-robot system has desirable characteristics for task performance. This design is based on model reference adaptive control, but of a nonstandard form. The net result is a controller with both adaptive impedance characteristics and assistive inputs that augment the human operator to provide improved task performance of the human-robot team. Simulations verify the performance of the proposed controller in a repetitive point-to-point motion task. Actual experimental implementations on a PR2 robot further corroborate the effectiveness of the approach.

Operator Dynamics Consideration for Less Conservative Coupled Stability Condition in Bilateral Teleoperation

Bilateral teleoperation control systems are designed for guaranteed stability against uncertainties in operator and environment dynamics. In this paper, we study the effect of human operator dynamics on the coupled stability by incorporating the operator dynamics in the master–slave network. We will analytically prove and graphically show that for any potentially unstable control architecture, as the operator minimum damping grows, the teleoperation system can stably tolerate a larger range of variations in the environment impedance parameters. More importantly, we will demonstrate how the proposed coupled stability analysis method can be utilized to design stabilizing controllers for enhanced transparency, given a priori knowledge or online estimate of human operator damping.

Human-Arm-and-Hand-Dynamic Model With Variability Analyses for a Stylus-Based Haptic Interface

Haptic interface research benefits from accurate human arm models for control and system design. The literature contains many human arm dynamic models but lacks detailed variability analyses. Without accurate measurements, variability is modeled in a very conservative manner, leading to less than optimal controller and system designs. This paper not only presents models for human arm dynamics but also develops inter- and intrasubject variability models for a stylus-based haptic device. Data from 15 human subjects (nine male, six female, ages 20-32) were collected using a Phantom Premium 1.5a haptic device for system identification. In this paper, grip-force-dependent models were identified for 1-3-N grip forces in the three spatial axes. Also, variability due to human subjects and grip-force variation were modeled as both structured and unstructured uncertainties. For both forms of variability, the maximum variation, 95 %, and 67 % confidence interval limits were examined. All models were in the frequency domain with force as input and position as output. The identified models enable precise controllers targeted to a subset of possible human operator dynamics.

Human-Oriented Control for Haptic Teleoperation

Haptic teleoperation enables the human to perform manipulation tasks in distant, scaled, hazardous, or inaccessible environments. The human closes the control loop sending haptic command signals to and receiving haptic feedback signals from the remote teleoperator. The main research question is how to design the control such that human decision making and action is supported in the best possible way while ensuring robust operation of the system. The human in the loop induces two major challenges for control design: 1) the dynamics of the human operator and the teleoperation system are tightly coupled, i.e., stability of the overall system is affected by the human operator dynamics; and 2) the performance of the teleoperation system is subjectively evaluated by the human, which typically means that standard control performance metrics are not suitable. This paper discusses recent control design successes in the area of haptic teleoperation. In particular, the importance and need of dynamic human haptic closed-loop behavior models and human perception models for the further improvement of haptic teleoperation systems is highlighted and discussed for real-world problem domains.

Human dynamics and stability of teleoperator systems with generalized projection-based force reflection algorithms

AbstractA new general stability result for networked bilateral teleoperator systems with projection-based force reflection is presented. Contrary to the previous results, the human operator dynamics are taken into account in the stability analysis. The human dynamics are assumed to satisfy a general condition formulated in terms of finite distance between output of the human dynamics and a certain “passivity-based” stabilizing set. In particular, this assumption allows for both passive and non-passive behaviour of the human operator. The overall stability of the bilateral teleoperator system is proven in the presence of network-induced communication constraints for an arbitrary projection-based force reflection algorithm from a broad class.

Diseño de un Controlador Híbrido en Ambientes Virtuales para Teleoperación

This article presents the design and implementation of an hybrid controller for a robotic teleoperation system. The low-level control structure is designed to control both, the position of the remote manipulator as well as the interaction force. In the local station the dynamics of the human operator and together with a model of a remote site included the environment. The supervisor controller is designed using the theory of hybrid systems and an automata was used for modeling the discrete event part. The theoretical results are validated through a simulation platform of a commercial robot.

An identification and grouping approach to analyze the output of a dynamic safety assessment

Dynamic Probabilistic Safety Assessment embeds models of the system process (typically thermo-hydraulic models) and of human operator dynamics within stochastic simulation engines. These engines generate sequences of component and operator action events, representing success, failures and other sources of variability. A challenge is to retrieve and organize the scenarios hidden in the large amount of information produced. The present paper discusses an approach for identifying and grouping the produced scenarios, based on possibilistic clustering classification; the aim is to single out the principal patterns of system evolution with respect not only to the final system states but also to the time of events and to the process evolution.

Simplified approach for modelling pilot pursuit control behaviour in multi-loop flight control tasks

A control-theoretic procedure for modelling human pilot pursuit control behaviour is presented. The procedure allows for the development of human pilot behavioural models in multi-loop flight control tasks in a simplified framework emphasizing frequency-domain techniques. Beginning with the primary control loops, each control loop is closed using a combination of output-rate feedback and output-error feedback. It is demonstrated that this approach can accommodate any vehicle dynamics that can be stabilized by a human pilot. In addition, the modelling approach identifies vehicle dynamics that approach the limits of human pilot controllability. The well-documented increase in pilot effective time delays that have been shown to accompany vehicle dynamics requiring lead compensation is also replicated by this modelling approach. A method for predicting handling-qualitiy levels that would be assigned to a particular vehicle and task is presented. A visual cue model is included, which can approximate the effects of degraded visual cues. It is shown that this model can be used to reproduce the three most important measurable effects of visual cue quality upon human operator dynamics, namely, an increase in ‘effective’ pilot time delay, a decrease in crossover frequency, and an increase in error-injected remnant. The ability of the modelling procedure to accommodate different levels of pilot aggressiveness in completing manoeuvres is demonstrated. Finally, an application to a multi-axis rotorcraft flight control problem is presented.

A fixed-order optimal control model of human operator response

Human operator models developed using optimal control theory are typically complicated and over-parameterized, even for simple controlled elements. The optimal projection (OP) synthesis technique is applied to a modified version of the optimal control model (OCM) of human operator dynamics. The result is a generalized formulation of a fixed-order modified optimal control model (FOMOCM) of the human operator and a computer algorithm that generates a FOMOCM when one exists. The FOMOCM forms a much needed bridge between high-order OCMs and traditional classical models.

Influence of the mechanical properties of a manipulandum on human operator dynamics. II. Viscosity.

The influence of the viscosity of a manipulandum used by a human operator in a position-control pursuit-tracking task was examined. An active servo-system was used to set the viscosity of a manipulandum (motor) connected to the forearm to one of seven levels ranging in a geometric series from 12 to 800 N.s/m. During each condition the viscosity of the motor was held constant by a computer while subjects tracked, by moving their forearm in the sagittal plane, a visually presented target whose position changed randomly every 1.5 s for 255 s. Nonparametric and parametric impulse response functions were calculated between the input (target) and output (position) in each tracking condition. Nonparametric analyses revealed that subjects became sluggish at higher viscosities (above 200 N.s/m) and took longer to reach the target. A second-order low-pass transfer function was found to provide a very good description of tracking performance at each viscous level. The gain and damping parameter of this transfer function were not affected by the manipulandum's viscosity, whereas both the pure delay and natural frequency of the human operator system decreased systematically with increasing manipulandum viscosity. These findings suggest that over the range of viscosities studied, there is no speed-accuracy trade-off in terms of determining an optimal level of manipulandum viscosity for a human operator, and that a less viscous interface will result in faster performance.

Influence of the mechanical properties of a manipulandum on human operator dynamics

An active servo-system was used to change the stiffness of a manipulandum used in a position-control pursuit-tracking task. The elastic stiffness of the manipulandum connected to the forearm was set by a computer at one of five levels ranging from 0 N/m to 2000 N/m. Subjects were required to track, either by moving their forearm or by generating a force isometrically, a visually presented target whose position changed randomly every second for 100 s. Nonparametric and parametric impulse response functions were calculated between the input (target) and output (force or position) in each tracking condition, and revealed that for all subjects force control was faster than position control when the stiffness of the manipulandum was set at 0 N/m. Subjects were also consistently faster in reaching the target when the stiffness was greater than zero, and were more accurate (steady-state response) when the stiffness of the manipulandum was set at lower rather than higher amplitudes. The parametric impulse response functions revealed that the human operator system was underdamped (0.7) with a natural frequency of approximately 8 rad/s. These findings were interpreted in terms of the responses of the various subsystems (visual, cognitive, contractile, limb mechanics) that comprise the human operator's response.

Modeling of task-dependent characteristics of human operator dynamics pursuit manual tracking

To model human operator (HO) dynamics in manual tracking tasks, an ensemble of models, each for a certain class of inputs, seems to be needed. By placing in a linear framework the modeling studies so far conducted, it is evident that different hypotheses have been proposed to explain the observed input dependence of the estimated HO (linear) models. Here, the authors examine these hypotheses and propose that the systemic notion of task dependence must be used to model this system. They have explored ways of deriving quantitative measures of the system task-dependent characteristics, using autoregressive moving-average (ARMA) models of input-output data obtained from a series of pursuit manual tracking experiments. These experiments utilized sum-of-sinusoids and random ternary inputs of various bandwidths. The resulting model parameters indicate significant task dependence of the HO dynamic characteristics. The effect of amplitude nonlinearities was examined and found to be statistically insignificant. >

Normalized predictive deconvolution - A time series algorithm for modeling human operator dynamics

A time series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of the system excitation signals used in the identification is not required. The approach is a multichannel identification technique for modeling multi-input/multioutput situations. The method presented includes statistical tests for validity, is designed for digital computation, and contains a new method for the determination of model order. A comprehensive relative power spectral density analysis may also be performed for validated models and the frequency response may be estimated for the operator. This method is applied to several sets of experimental data where the results are discussed and shown to provide considerable insight into overall system behavior. New results are also presented for a multi-input task that has not been previously modeled to demonstrate the strengths of the method.

Application of Time-Series Modeling to Human Operator Dynamics

Time-series analysis is applied to model human operator dynamics in pursuit and compensatory tracking modes. The normalized residual criterion is used as a one-step analytical tool to encompass the processes of identification, estimation, and diagnostic checking. A parameter constraining technique is introduced to develop more reliable models of human operator dynamics. The human operator is adequately modeled by a second-order dynamic system both in pursuit and compensatory tracking modes. In comparing the data sampling rates, 100 ms between samples is adequate and is shown to provide better results than a 200 ms sampling. The residual power spectrum and eigenvalue analysis show that the human operator is not a generator of periodic characteristics.

Human operator dynamics in manual tracking systems with auditory input.

Response characteristics of human operators in manual pursuit tracking with auditory input are investigated. The human operator hears in his left ear a sound whose frequency varies in proportion to an external random signal. At the same time, he hears in his right ear another sound whose frequency varies in proportion to the angle of a control lever of a potentiometer. The operator controls the angle of the lever so that the frequencies, of the sounds in both ears remain as close as possible. The dynamics of the human operator is studied by assuming a "man-machine system" whose input is the external signal and whose output is the voltage of the potentiometer. A learning identification method proposed by one of the authors is used to calculate the weighting function of the man-machine system, which is displayed on a CRT screen in renal time. During the tracking task, the skin potential activity (SPA) is measured as an index of arousal of the operator.

Human Operator Dynamics in Manual Tracking Systems with Auditory Input

Human Operator Dynamics in Manual Tracking Systems with Auditory Input