Dual-Task Performance as a Function of Individual Alarm Validity and Alarm System Reliability Information

1996 ◽  
Vol 40 (23) ◽  
pp. 1237-1241 ◽  
Author(s):  
James P. Bliss ◽  
Sonya M. Jeans ◽  
Heidi J. Prioux
Keyword(s):  
Real Time ◽  
Undergraduate Students ◽  
System Reliability ◽  
Tracking Error ◽  
Alarm System ◽  
Alarm Response ◽  
Dual Task Performance ◽  
Prior Literature ◽  
Response Consistency ◽  
Speed Accuracy

Researchers and designers have investigated ways to mitigate the consequences of alarm mistrust, including using redundant information sources to ensure response consistency. Research concerning the benefit of this practice has not considered the operator's prior alarm system knowledge, or the division of attention among multiple tasks. We investigated the influence of real-time individual alarm validity information and prior alarm system reliability information on primary and alarm task responses. One hundred undergraduate students performed a continuous compensatory tracking task while responding to microcomputer-based alarms. Dependent measures included alarm response frequency, speed, accuracy, and appropriateness, and primary task tracking error. Results indicated that participants with real-time alarm validity information responded less frequently, but more appropriately than those without such information. Participants with prior access to alarm system reliability information responded more frequently than those without such information. The results are discussed as they apply to prior literature and alarm system design.

scholarly journals Implementation and intelligent gain tuning feedback–based optimal torque control of a rotary parallel robot

2021 ◽  
pp. 107754632110191
Author(s):  
Farzam Tajdari ◽  
Naeim Ebrahimi Toulkani
Keyword(s):  
Real Time ◽  
Tracking Error ◽  
Parallel Robot ◽  
Torque Control ◽  
Test Bed ◽  
Linear Quadratic ◽  
Control Effort ◽  
The Real ◽  
Unknown Disturbances ◽  
Quadratic Integral

Aiming at operating optimally minimizing error of tracking and designing control effort, this study presents a novel generalizable methodology of an optimal torque control for a 6-degree-of-freedom Stewart platform with rotary actuators. In the proposed approach, a linear quadratic integral regulator with the least sensitivity to controller parameter choices is designed, associated with an online artificial neural network gain tuning. The nonlinear system is implemented in ADAMS, and the controller is formulated in MATLAB to minimize the real-time tracking error robustly. To validate the controller performance, MATLAB and ADAMS are linked together and the performance of the controller on the simulated system is validated as real time. Practically, the Stewart robot is fabricated and the proposed controller is implemented. The method is assessed by simulation experiments, exhibiting the viability of the developed methodology and highlighting an improvement of 45% averagely, from the optimum and zero-error convergence points of view. Consequently, the experiment results allow demonstrating the robustness of the controller method, in the presence of the motor torque saturation, the uncertainties, and unknown disturbances such as intrinsic properties of the real test bed.

scholarly journals On the Performance of One-Stage and Two-Stage Object Detectors in Autonomous Vehicles Using Camera Data

2020 ◽  
Vol 13 (1) ◽  
pp. 89
Author(s):  
Manuel Carranza-García ◽  
Jesús Torres-Mateo ◽  
Pedro Lara-Benítez ◽  
Jorge García-Gutiérrez
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Autonomous Vehicles ◽  
Remote Sensing Data ◽  
Autonomous Driving ◽  
Two Stage ◽  
Detection Systems ◽  
One Stage ◽  
Time Requirements ◽  
Speed Accuracy

Object detection using remote sensing data is a key task of the perception systems of self-driving vehicles. While many generic deep learning architectures have been proposed for this problem, there is little guidance on their suitability when using them in a particular scenario such as autonomous driving. In this work, we aim to assess the performance of existing 2D detection systems on a multi-class problem (vehicles, pedestrians, and cyclists) with images obtained from the on-board camera sensors of a car. We evaluate several one-stage (RetinaNet, FCOS, and YOLOv3) and two-stage (Faster R-CNN) deep learning meta-architectures under different image resolutions and feature extractors (ResNet, ResNeXt, Res2Net, DarkNet, and MobileNet). These models are trained using transfer learning and compared in terms of both precision and efficiency, with special attention to the real-time requirements of this context. For the experimental study, we use the Waymo Open Dataset, which is the largest existing benchmark. Despite the rising popularity of one-stage detectors, our findings show that two-stage detectors still provide the most robust performance. Faster R-CNN models outperform one-stage detectors in accuracy, being also more reliable in the detection of minority classes. Faster R-CNN Res2Net-101 achieves the best speed/accuracy tradeoff but needs lower resolution images to reach real-time speed. Furthermore, the anchor-free FCOS detector is a slightly faster alternative to RetinaNet, with similar precision and lower memory usage.

Synergistic real-time compensation of tracking and contouring errors for precise parametric curved contour following systems

2017 ◽  
Vol 232 (19) ◽  
pp. 3367-3383 ◽  
Author(s):  
De-Ning Song ◽  
Jian-Wei Ma ◽  
Zhen-Yuan Jia ◽  
Feng-Ze Qin ◽  
Xiao-Xuan Zhao
Keyword(s):  
Real Time ◽  
High Precision ◽  
Tracking Error ◽  
Estimation Algorithm ◽  
Computer Numerical Control ◽  
Numerical Control ◽  
System Structure ◽  
Parametric Curve ◽  
Contouring Error ◽  
Contour Following

The tracking and contouring errors are inevitable in real computer numerical control contour following because of the reasons such as servo delay and dynamics mismatch. In order to improve the motion accuracy, this paper proposes a synergistic real-time compensation method of tracking and contouring errors for precise parametric curve following of the computer numerical control systems. The tracking error for each individual axis is first compensated, by using the feed-drive models with the consideration of model uncertainties, to enhance the tracking performances of all axes. Further, the contouring error is estimated and compensated to improve the contour accuracy directly, where a high-precision contouring-error estimation algorithm, based on spatial circular approximation of the desired contour neighboring the actual motion position, is presented. Considering that the system structure is coupled after compensation, the stability of the coupled system is analyzed for design of the synergistic compensator. Innovative contributions of this study are that not only the contouring-error can be estimated with a high precision in real time, but also the tracking and contouring performances can be simultaneously improved although there exist modeling errors and disturbances. Simulation and experimental tests demonstrate the effectiveness and advantages of the proposed method.

scholarly journals A model reference adaptive variable impedance control method for robot

2021 ◽  
Vol 336 ◽  
pp. 03005
Author(s):  
Xinchao Sun ◽  
Lianyu Zhao ◽  
Zhenzhong Liu
Keyword(s):  
Real Time ◽  
Tracking Control ◽  
Control Method ◽  
Impedance Control ◽  
Tracking Error ◽  
Reference Trajectory ◽  
Control Parameters ◽  
Model Reference ◽  
Force Tracking ◽  
Model Reference Adaptive

As a simple and effective force tracking control method, impedance control is widely used in robot contact operations. The internal control parameters of traditional impedance control are constant and cannot be corrected in real time, which will lead to instability of control system or large force tracking error. Therefore, it is difficult to be applied to the occasions requiring higher force accuracy, such as robotic medical surgery, robotic space operation and so on. To solve this problem, this paper proposes a model reference adaptive variable impedance control method, which can realize force tracking control by adjusting internal impedance control parameters in real time and generating a reference trajectory at the same time. The simulation experiment proves that compared with the traditional impedance control method, this method has faster force tracking speed and smaller force tracking error. It is a better force tracking control method.

A Highly Reliable Online Monitoring and Real-Time Alarm System for the Insulation Condition of Power Transformers

2014 ◽  
Vol 971-973 ◽  
pp. 1045-1050
Author(s):  
Wen Xing Sun ◽  
Zhao Hui Li ◽  
Shi Jie Cheng
Keyword(s):  
Electric Power ◽  
Real Time ◽  
Condition Monitoring ◽  
Online Monitoring ◽  
Hydropower Plant ◽  
Power Transformers ◽  
Monitoring Systems ◽  
Alarm System ◽  
Condition Monitoring Systems ◽  
Insulation Condition

Many successful applications for the online monitoring of the insulation condition for electric power transformers have been reported over last thirty years. However, false or unsolved alarms have been quite frequently generated by those condition monitoring systems. Failures and some occasionally catastrophic accidents involving transformers have still occurred. A highly reliable insulation condition online monitoring and real-time alarm system has been developed, to help resolve these problems. An electric power transformer has strongly linked mechanical, electrical, magnetic, chemical and thermal characteristics, and is also directly linked to circuit breakers and generators. Team Intelligence (TI) was employed to integrate all the monitoring modules of the various different aspects of the transformer into one unique system. This system could also be integrate with the condition monitoring systems of various linked facilities, such as the monitoring systems of the turbine and the generator in a Optimal Maintenance Information System for Hydropower Plant (HOMIS). Highly reliable monitoring and real-time alarms of transformer insulation condition could be achieved, due to highly coordinated and rapid response features. This system has been deployed in several hydropower plants. The industrial application examples are demonstrated.

Analysis of Reliability Requirements for Fire Alarm Systems Operated in Civil Structures and Critical Infrastructure Facilities

2020 ◽  
Vol 69 (3) ◽  
pp. 77-87
Author(s):  
Krzysztof Jakubowski
Keyword(s):  
System Reliability ◽  
Critical Infrastructure ◽  
Alarm System ◽  
Civil Structures ◽  
Fire Hazards ◽  
Fire Alarm ◽  
Alarm Systems ◽  
Fire Alarm System

A fire alarm system (FAS) is one of the most important safety facilities used in any building, and include CCTV and intrusion and panic alarms. Pursuant to the Polish Regulation of the Minister of the Interior and Administration of 07/06/2010, FASs are required in specific civil structures. FASs are directly responsible for the protection of the life and health of humans and animals, and indi-rectly for property at the protected sites. In considering the fire hazards and scenarios, a FAS should be characterized with sufficient reliability. Every FAS is subject to specific requirements in terms of reliability and continuity of performance at the stages of monitoring, FAS failure, and fire. This work is an analysis of the reliability requirements for FAS. Keywords: fire alarm system, reliability requirements, structures.

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