【作者】 朱丽花；

【导师】 张建华；

【作者基本信息】 华东理工大学 ， 控制科学与工程， 2012， 硕士

【摘要】 在复杂人机系统中,操作员功能状态(Operator Functional States, OFS)是影响系统安全性的一个重要因素。本文基于aCAMS仿真系统实验中采集到的一系列操作员电生理信号及性能数据,采用协同进化模糊(Fuzzy Cooperative Coevolutionary, FCC)建模方法建立OFS模型,实现对OFS的评估及预测。该方法将模糊模型的主要因素,如模糊规则的前件/后件、隶属函数参数编码为不同的种群,同时优化模糊模型的结构与参数,算法中种群个体适应度函数同时考虑模型的精确性和解释性,采用分量加权求和法将多目标优化转化为单目标优化。首先将该方法用于几个UCI标准分类数据集的的建模仿真,验证该建模方法的通用有效性。然后针对于OFS建模中5个EEG和ECG指标对不同被试OFS的敏感度不同,通过Simba算法计算这些指标的重要性来进行变量选择,确定OFS模型的初始结构,再用协同进化算法对其进行结构和参数上的优化。最后的建模结果表明,协同进化模糊建模方法用于OFS的建模是有效的,优化后的模型精度在可接受范围内,所涉及的模糊规则和模糊子集总数较之优化前均有较大幅度的减少,模型结构得到了简化,模型兼具良好的精确性和可解释性。与基于GA的建模方法相比,FCC用于OFS建模展现了更加优越的性能,所建立的模型基本能反应OFS的实际变化趋势,具有一定的预测能力,可用于自适应系统中,根据模型预测结果,适时调整系统控制策略,从而实现智能化人机交互系统。更多还原

【Abstract】 Operator Functional State (OFS) is an important factor that affect system security in complex human-machine system. This paper adopts Fuzzy Cooperative Co-evolutionary (FCC) modeling algorithm to establish OFS models based on a series of electrophysiological signals and operator performance data. This method encode the main parameters of fuzzy model in different populations, such as the antecedent/post of fuzzy rules, membership function parameters, to optimize model structure and parameters synchronously. The individual fitness function in algorithm populations consider both of model accuracy and interpretability by using a components weighted-sum method which transit multi-objective optimization into single-objective optimization. FCC method is used to establish fuzzy classification systems for five UCI data sets before OFS modeling. And the simulation results verified its effectiveness. According to the sensitivities of EEG and ECG markers of different operators are different, a Simba method is adapted to select input variables. The simulation results show that each OFS fuzzy model has good accuracy and simplified structure, evolves less rules and fuzzy sets. Comparison to GA fuzzy modeling method, FCC has better generalization performance for establishing OFS model. The final model based on the results is used to adjust control strategies, achieving intelligent human-computer interaction.更多还原