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.
All Science Journal Classification (ASJC) codes
- Artificial Intelligence