Human-machine Control System Research Articles

Features of simulation of operator control of unmanned aerial vehicle and its target load

The article is devoted to the formulation of the problem of synthesis of the control system of an unmanned aerial vehicle (UAV) with the participation of a human operator. An analysis is made of various approaches to the synthesis of systems, models of a human operator as a link in a tracking system, mathematical models and information support for complex human-machine systems, competencies required by UAV operators. The system considers a human operator as a dynamic link that performs compensatory monitoring of the relevant information that is presented on the monitor of the corresponding operator controlling the UAV or its target load in accordance with the task. On the basis of the analysis, a generalized scheme of the UAV control system and its target load is substantiated, a mathematical model of a human operator is studied in the form of a transfer function consisting of five elementary links that take into account the dynamic characteristics of the central nervous system, the delay of the neuromuscular system, the ability of the human operator to smooth random fluctuations of the information presented on the monitor screen received from the telemetry system. As a typical example of a human-machine control system, the ground control point of the multifunctional unmanned aerial complex “Busel” is considered, which includes two workplaces for the UAV control operator and the target load control operator, which is considered equipment designed to monitor objects located on the earth’s surface

АЛГОРИТМИЧЕСКОЕ ОБЕСПЕЧЕНИЕ ИНТЕРФЕЙСА УПРАВЛЕНИЯ РОБОТ-ЧЕЛОВЕК ПРИ ВЫДЕЛЕНИИ ЗРИТЕЛЬНЫХ ВЫЗВАННЫХ ПОТЕНЦИАЛОВ НА ОСНОВЕ МНОГОМЕРНОГО ИНДЕКСА СИНХРОНИЗАЦИИ

The aim of the study is to build human-machine control systems. The main methods for con-structing such systems, methods for isolating evoked potentials in electroencephalograms. The article presents studies of electroencephalogram signals with steady state visual evoked potentials for different frequencies of photostimulation, based on the method of multivariate synchronization index. The influence of the length of the processed window on the accuracy of recognition of the frequency of the studied signal is considered. In the course of research, the authors verify the need for pre-processing of the original signals by means of bandpass signal filtering. In addition, the possibility of using a multi-dimensional synchronization index in multi-channel mode is being considered. The result of the authors study is recommendations on the parameters used to high-light the established visual evoked potentials in the method of multivariate synchronization index. The possibility of using algorithms based on a multivariate synchronization index in real time is shown. The results obtained are of practical importance, since they can be used to build neurocomputer interfaces based on visual evoked potentials and can be further used in the for-mation of control theory of robotic systems for various purposes and in the implementation of solutions for the organization of human-machine interaction in narrow practical problems.

Pattern Classification of Human Cognitive State in Man-Machine Systems Using Multiple Sources of Pyschophysiological Data and Fuzzy Clustering Approach

The primary goal of this work is to classify Human Cognitive State (HCS) in human-machine cooperative control systems. A total of 10 young and fit volunteers were used as the experimental subjects. A set of 9 process control task conditions were programmed on an automation-enhanced Cabin Air Management System (aCAMS) originally developed to simulate with high-fidelity the life support system in aerospace applications. The psychophysiological and performance data of the subjects were recorded while they performed process control operations in collaboration with computer-based automatic control systems. The fuzzy C-Means (FCM) algorithm was used to classify the momentary HCSs into three categories: “Good”, “Average” and “Risky” with certain degree of membership. The classification results indicated that the FCM-based classifier can achieve accurate HCS classification if the influential features are properly selected. The method proposed has potential to be applied to design adaptive task (or functional) allocation strategy in adaptive/intelligent human-machine control systems.

A Three-Component Model of the Control Error in Manual Tracking of Continuous Random Signals

The performance of human operators acting within closed-loop control systems is investigated in a classic tracking task. The dependence of the control error (tracking error) on the parameters display gain, k(display), and input signal frequency bandwidth, f(g), which alter task difficulty and presumably the control delay, is studied with the aim of functionally specifying it via a model. The human operator as an element of a cascaded human-machine control system (e.g., car driving or piloting an airplane) codetermines the overall system performance. Control performance of humans in continuous tracking has been described in earlier studies. Using a handheld joystick, 10 participants tracked continuous random input signals. The parameters f(g) and k(display) were altered between experiments. Increased task difficulty promoted lengthened control delay and, consequently, increased control error.Tracking performance degraded profoundly with target deflection components above 1 Hz, confirming earlier reports. The control error is composed of a delay-induced component, a demand-based component, and a novel component: a human tracking limit. Accordingly, a new model that allows concepts of the observed control error to be split into these three components is suggested. To achieve optimal performance in control systems that include a human operator (e.g., vehicles, remote controlled rovers, crane control), (a) tasks should be kept as simple as possible to achieve shortest control delays, and (b) task components requiring higher-frequency (> 1 Hz) tracking actions should be avoided or automated by technical systems.

An adaptive human–machine control system based on multiple fuzzy predictive models of operator functional state

Under the framework of adaptive Human–Machine (HM) systems, it has been proposed that human operators’ task level should be dynamically adjusted according to his/her functional state. The construction of models that can reliably predict the operator functional state (OFS) becomes critical to accomplish such adjustments. However, most of the existing models that evaluate the current OFS by using operators’ current physiological data are static and are of no real predictive capability. Thus, when they are used in adaptive HM systems, the resultant task allocation between operators and machines would be time-delayed. To overcome this problem, a one-step-ahead predictive model concept for OFS computation is proposed. Meanwhile, multiple fuzzy models are developed by using the Wang–Mendel method. These models are able to increase the accuracy of the OFS breakdown prediction, as well as to reduce the model training time. In addition, an adaptive task allocation strategy is designed to validate the proposed models. The results demonstrate that, compared to the conventional HM systems, a 6.7% OFS increment and a 57.1% OFS breakdown decrement can be obtained in the multiple models based adaptive HM systems. The multiple predictive models and the adaptive task allocation strategy would pave the way for future implementations of real-time adaptive HM systems.

A Study of Ergonomic Measurement Indices in Evaluating Human-Machine Interfaces

Measurement and evaluation of a human-machine interface is a difficult yet very important issue. The difficulty lies in that the issue is inherently a very subjective, and the importance is that the evaluation is part of design process for systems development. The purpose of evaluation is to see how an interface affects the operation of a human-machine control system in two aspects: the operator's mental workload and the performance in completing tasks. In this paper primarily the eye behaviors measure is discussed, together with some other measures, for evaluating two interface design frameworks: Ecological Interface Design (EID) and Function Behavior State (FBS). The measures we used cover both the measure for mental workload and the measure for performance. It is observed through the experiment that these measures vary in different degrees of sensitivity to the hypothesis under investigation and are sometimes in conflict. This has given a motivation for a further study on a new issue called ‘measure fusion’. This further study is briefly discussed.

人間-機械制御系における手先位置制御に関する人間の開ループ整形特性

人間-機械制御系における手先位置制御に関する人間の開ループ整形特性