An intelligent fuzzy control system with adapted interval for improving the supervisory performance in automation

Autor: Cheng-Li Liu, Shiaw-Tsyr Uang, Shun-Chi Kuo
Rok vydání: 2017
Předmět:
Zdroj: Operational Research. 18:689-709
ISSN: 1866-1505
1109-2858
DOI: 10.1007/s12351-017-0336-3
Popis: Monitoring responsibilities include checking the automated operating system to make judgments and provide solutions. A loss of vigilance will lead to accidents if care is not taken. Therefore, emergency situations need to be quickly detected. The purpose of this study was to develop an intelligent fuzzy control system by using fuzzy sets to evaluate and improve the performance of supervisors. There are two input variables: fuzzy set $$\tilde{S}$$ , which represents the linguistic notion “hit” when supervisor action is needed, and the fuzzy set N, which represents the linguistic notion “false alarm” when no action is needed. The evaluation was extended from a two-value logic to a multi-value logic by using membership functions. The experimental results show that the fuzzy control used to evaluate the domain of decision response, i.e., the differences among a Type I error (miss), a Type II error (false alarm) and an appropriate reaction, was effective. Therefore, the traditional two-values logic was expanded to the multiple-values performance evaluation to clearly describe the difference in the judgment needed when monitoring “also this also other” work. In addition an alarm signal was produced by the fuzzy system for reminding participant’s attention. According to the results, the alarm was adapted to call the operator’s attention when a situation needed action to improve the supervisory performance. The results show that the effect of the fuzzy control alarm system for improving supervisory performance is significant. Additionally, the wide interval defined in fuzzy set would be more efficient to call participant’s attention and improve performance significantly than narrow.
Databáze: OpenAIRE
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