为解决生态保护红线监管工作中查询难、定位难、判别难的问题,精准落实生态保护红线空间位置,全面获取生态保护红线台账资料,快速定位督察点坐标是核心与关键。传统监管模式依赖人工作业,时空差异大、工作烦琐、耗时费力。该文基于移动...为解决生态保护红线监管工作中查询难、定位难、判别难的问题,精准落实生态保护红线空间位置,全面获取生态保护红线台账资料,快速定位督察点坐标是核心与关键。传统监管模式依赖人工作业,时空差异大、工作烦琐、耗时费力。该文基于移动GIS技术,以Xcode为研发平台,结合ArcGIS Runtime for iOS进行二次开发,设计并研发镇江市生态保护红线监管系统。系统搭载于智能平板设备(iPad),具备生态保护红线信息查询、督察点位分析、导航定位、法规宣传等功能。方便用户快速、准确地获取生态保护红线的相关信息,实现了生态保护红线的高效监管。系统具备功能全面、操作简便、实用性强等优势,现于镇江市生态环境局、镇江市自然资源和规划局及各区县分局推广使用,效果反馈良好。该系统为生态保护红线区域的日常监管工作提供了便利,推进了生态保护红线监管工作的移动化发展。展开更多
An analytical tuning method was proposed for fuzzy PID controller used in Smith predictor in order to extend its application and improve its robustness. The fuzzy PID controller was expressed as a sliding mode control...An analytical tuning method was proposed for fuzzy PID controller used in Smith predictor in order to extend its application and improve its robustness. The fuzzy PID controller was expressed as a sliding mode control. Based on Lyapunov theory, Smith predictor was analyzed in time domain. The parameters of the fuzzy PID controller can be obtained using traditional linear control theory and sliding mode control theory. The simulation experiments were implemented. The simulation results show that the control performance, robustness and stability of the fuzzy PID controller are better than those of the PID controller in Smith predictor.展开更多
文摘为解决生态保护红线监管工作中查询难、定位难、判别难的问题,精准落实生态保护红线空间位置,全面获取生态保护红线台账资料,快速定位督察点坐标是核心与关键。传统监管模式依赖人工作业,时空差异大、工作烦琐、耗时费力。该文基于移动GIS技术,以Xcode为研发平台,结合ArcGIS Runtime for iOS进行二次开发,设计并研发镇江市生态保护红线监管系统。系统搭载于智能平板设备(iPad),具备生态保护红线信息查询、督察点位分析、导航定位、法规宣传等功能。方便用户快速、准确地获取生态保护红线的相关信息,实现了生态保护红线的高效监管。系统具备功能全面、操作简便、实用性强等优势,现于镇江市生态环境局、镇江市自然资源和规划局及各区县分局推广使用,效果反馈良好。该系统为生态保护红线区域的日常监管工作提供了便利,推进了生态保护红线监管工作的移动化发展。
基金Project(70473068) supported by the National Natural Science Foundation of ChinaProject(05JZD00024) supported by the Major Subject of Ministry of Education, China
文摘An analytical tuning method was proposed for fuzzy PID controller used in Smith predictor in order to extend its application and improve its robustness. The fuzzy PID controller was expressed as a sliding mode control. Based on Lyapunov theory, Smith predictor was analyzed in time domain. The parameters of the fuzzy PID controller can be obtained using traditional linear control theory and sliding mode control theory. The simulation experiments were implemented. The simulation results show that the control performance, robustness and stability of the fuzzy PID controller are better than those of the PID controller in Smith predictor.