电梯集群控制系统可根据乘客呼梯信号作出最有利的响应,以实现呼梯人员的目的。针对当前自动化远程监控应用水平较低及电梯异常情况频繁出现的情况,构建了一个基于WinCC(Windows Control Center,视窗控制中心)、最小等待时间电梯群控调...电梯集群控制系统可根据乘客呼梯信号作出最有利的响应,以实现呼梯人员的目的。针对当前自动化远程监控应用水平较低及电梯异常情况频繁出现的情况,构建了一个基于WinCC(Windows Control Center,视窗控制中心)、最小等待时间电梯群控调度算法、S7-1200 PLC、PC的一套电梯监控系统。所设计的系统能够实现集中运行和远程监控,在WinCC平台完成电梯用户登录系统、电梯运行状态监控子界面设计、关键数据报表输出功能,最后利用电梯仿真平台对系统进行了验证测试。仿真测试结果显示,所设计的控制系统稳定可靠。展开更多
A hybrid optimization approach combining a particle swarm algorithm, a genetic algorithm, and a heuristic interleaving algorithm is proposed for scheduling tasks in the multifunction phased array radar. By optimizing ...A hybrid optimization approach combining a particle swarm algorithm, a genetic algorithm, and a heuristic interleaving algorithm is proposed for scheduling tasks in the multifunction phased array radar. By optimizing parameters using chaos theory, designing the dynamic inertia weight for the particle swarm algorithm as well as introducing crossover operation and mutation operation of the genetic algorithm, both the efficiency and exploration ability of the hybrid algorithm are improved. Under the frame of the intelligence algorithm, the heuristic interleaving scheduling algorithm is presented to further use the time resource of the task waiting duration. A large-scale simulation demonstrates that the proposed algorithm is more robust and efficient than existing algorithms.展开更多
文摘电梯集群控制系统可根据乘客呼梯信号作出最有利的响应,以实现呼梯人员的目的。针对当前自动化远程监控应用水平较低及电梯异常情况频繁出现的情况,构建了一个基于WinCC(Windows Control Center,视窗控制中心)、最小等待时间电梯群控调度算法、S7-1200 PLC、PC的一套电梯监控系统。所设计的系统能够实现集中运行和远程监控,在WinCC平台完成电梯用户登录系统、电梯运行状态监控子界面设计、关键数据报表输出功能,最后利用电梯仿真平台对系统进行了验证测试。仿真测试结果显示,所设计的控制系统稳定可靠。
基金Project supported by the National Natural Science Foundation of China （Nos. 61503408 and 61601504）
文摘A hybrid optimization approach combining a particle swarm algorithm, a genetic algorithm, and a heuristic interleaving algorithm is proposed for scheduling tasks in the multifunction phased array radar. By optimizing parameters using chaos theory, designing the dynamic inertia weight for the particle swarm algorithm as well as introducing crossover operation and mutation operation of the genetic algorithm, both the efficiency and exploration ability of the hybrid algorithm are improved. Under the frame of the intelligence algorithm, the heuristic interleaving scheduling algorithm is presented to further use the time resource of the task waiting duration. A large-scale simulation demonstrates that the proposed algorithm is more robust and efficient than existing algorithms.
