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GA-based actuator control method for minimizing power consumption in cyber physical systems

机译:基于遗传算法的执行器控制方法,用于最小化网络物理系统中的功耗

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摘要

In recent years, the public has been paying ever greater attention to problems associated with energy production and consumption. Energy-supply issues rightly constitute one of the most important issues that we face. In the absence of any viable alternative energy supply, a strategy that would result in energy savings is a legitimate goal. In this paper, we propose a genetic algorithm-based method by which electrical operators in a cyber physical system could be scheduled and controlled. Our method accounts for not only process output but also environmental variation. We propose that the electrical operators be of the same function but with different capabilities. One set of sensors would be placed dispersedly around the to-be-affected area for measuring the output of the processes. Another set of sensors would collect the environmental variation value for prediction purposes. The simulation results show that the application of our proposed GA-based Actuator Control (GAAC) method to the aforementioned cyber physical system can minimize its power consumption while accomplishing the desired set point.
机译:近年来,公众越来越关注与能源生产和消费有关的问题。能源问题正确地构成了我们面临的最重要的问题之一。在没有任何可行的替代能源供应的情况下,一种能够节省能源的战略是一个合理的目标。在本文中,我们提出了一种基于遗传算法的方法,通过该方法可以调度和控制网络物理系统中的电气运营商。我们的方法不仅考虑过程输出,还考虑环境变化。我们建议电气操作员具有相同的功能,但功能不同。一组传感器将散布在要受影响的区域周围,以测量过程的输出。另一组传感器将收集环境变化值以用于预测目的。仿真结果表明,将我们提出的基于遗传算法的执行器控制(GAAC)方法应用于上述网络物理系统可以在实现所需设定点的同时将其功耗降至最低。

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