中文摘要：

在高安全性要求的复杂人机系统中,为了保证系统安全运行,需要对操作员功能状态（Operator Functional State,OFS）进行有效的监测和评估,以防止因操作员状态失效而产生的事故。本文使用基于粒子群优化（Particle Swarm Optimization,PSO）的Wang-Mendel（WM）方法建立起操作员电生理信号与OFS之间的模糊模型,对采用两种不同的规则提取策略的建模结果比较表明,本文使用的混合规则提取策略可以对OFS进行更有效的评估。

英文摘要：

In the safety-critical complex human-machine systems, in order to keep the systems running safely, it is necessary to monitor and analyze the operator functional state （OFS） efficiently to prevent the potential accidents. In this paper, we use the Particle Swarm Optimization （PSO） based Wang-Mendel （WM） method to build the fuzzy OFS model by using the operator electrophysiological signals. Compared to the results of WM based OFS model with conventional rule extraction strategy, the hybrid rule extraction strategy used in this paper can achieve better results. As a preliminary research for the OFS modeling, this paper provides a model support for the future application of the adaptive human-machine automation system.