为探究在集散式控制系统(distributed control system,DCS)危险排除过程中控制员不同信息搜索策略对排险任务绩效的影响及认知负荷的中介效应,基于虚拟现实技术、皮肤电采样和眼动追踪技术构建模拟DCS工控平台,招募20名相关专业被试参...为探究在集散式控制系统(distributed control system,DCS)危险排除过程中控制员不同信息搜索策略对排险任务绩效的影响及认知负荷的中介效应,基于虚拟现实技术、皮肤电采样和眼动追踪技术构建模拟DCS工控平台,招募20名相关专业被试参与模拟排险实验并对其认知负荷及排险绩效进行量化,使用眼动轨迹匹配法判断被试的信息搜索模式,研究认知负荷的中介效应及中介机理。研究结果表明:不同信息搜索策略会显著影响任务绩效;认知负荷对该影响的中介效应高达89.66%,表明信息搜索策略主要通过影响认知负荷来间接作用于排险任务绩效,认知负荷越高,任务绩效越低;逻辑系统搜索策略能通过高效图式匹配减少认知资源消耗,显著抑制认知负荷增长,任务绩效表现最佳;空间系统搜索较难抑制认知负荷,任务绩效较差;随机搜索被试认知负荷显著高于其他组,绩效表现最差;此外,不同认知负荷水平下被试的信息搜索策略没有明显转变倾向。研究结果可为DCS控制人员的考核和培训提供理论支撑。展开更多
A new adaptive neural network（NN） output-feedback stabilization controller is investigated for a class of uncertain stochastic nonlinear strict-feedback systems with discrete and distributed time-varying delays and ...A new adaptive neural network（NN） output-feedback stabilization controller is investigated for a class of uncertain stochastic nonlinear strict-feedback systems with discrete and distributed time-varying delays and unknown nonlinear functions in both drift and diffusion terms.First,an extensional stability notion and the related criterion are introduced.Then,a nonlinear observer to estimate the unmeasurable states is designed,and a systematic backstepping procedure to design an adaptive NN output-feedback controller is proposed such that the closed-loop system is stable in probability.The effectiveness of the proposed control scheme is demonstrated via a numerical example.展开更多
文摘为探究在集散式控制系统(distributed control system,DCS)危险排除过程中控制员不同信息搜索策略对排险任务绩效的影响及认知负荷的中介效应,基于虚拟现实技术、皮肤电采样和眼动追踪技术构建模拟DCS工控平台,招募20名相关专业被试参与模拟排险实验并对其认知负荷及排险绩效进行量化,使用眼动轨迹匹配法判断被试的信息搜索模式,研究认知负荷的中介效应及中介机理。研究结果表明:不同信息搜索策略会显著影响任务绩效;认知负荷对该影响的中介效应高达89.66%,表明信息搜索策略主要通过影响认知负荷来间接作用于排险任务绩效,认知负荷越高,任务绩效越低;逻辑系统搜索策略能通过高效图式匹配减少认知资源消耗,显著抑制认知负荷增长,任务绩效表现最佳;空间系统搜索较难抑制认知负荷,任务绩效较差;随机搜索被试认知负荷显著高于其他组,绩效表现最差;此外,不同认知负荷水平下被试的信息搜索策略没有明显转变倾向。研究结果可为DCS控制人员的考核和培训提供理论支撑。
基金supported by the National Natural Science Fundation of China (6080402160974139+3 种基金61075117)the Fundamental Research Funds for the Central Universities (JY10000970001K5051070000272103676)
文摘A new adaptive neural network（NN） output-feedback stabilization controller is investigated for a class of uncertain stochastic nonlinear strict-feedback systems with discrete and distributed time-varying delays and unknown nonlinear functions in both drift and diffusion terms.First,an extensional stability notion and the related criterion are introduced.Then,a nonlinear observer to estimate the unmeasurable states is designed,and a systematic backstepping procedure to design an adaptive NN output-feedback controller is proposed such that the closed-loop system is stable in probability.The effectiveness of the proposed control scheme is demonstrated via a numerical example.
